[{"data":1,"prerenderedAt":1197},["ShallowReactive",2],{"member-staff\u002Fruibin-bai-en":3,"member-publications-staff\u002Fruibin-bai":73},{"_path":4,"_dir":5,"_draft":6,"_partial":6,"_locale":7,"title":8,"description":9,"name":10,"role":11,"department":12,"interests":13,"body":15,"_type":63,"_id":64,"_source":65,"_file":66,"_stem":67,"_extension":68,"locale":69,"image":70,"category":5,"orcid":71,"order":72},"\u002Fmembers\u002Fstaff\u002Fruibin-bai","staff",false,"","Professor","浙江省自然科学基金杰青；浙江省\"钱江人才\"计划；浙江省高等学校中青年学科带头人；英国诺丁汉大学博士（PhD, University of Nottingham, UK）。SCI 期刊 EJOR、TEVC、Networks 编委。高质量学术论文 110 余篇，包括 TRB、INFORMS JOC 等 A 类期刊；主持国家自然基金及省市项目 20 余项，科研经费 1400 余万元；培养博士生 10 余名。","Ruibin Bai","Director of Lab","Department of Computer Science",[14],"Computer Science and Operations Research",{"type":16,"children":17,"toc":60},"root",[18],{"type":19,"tag":20,"props":21,"children":22},"element","p",{},[23,26,32,34,39,40,45,47,52,53,58],{"type":24,"value":25},"text","浙江省自然科学基金杰青；浙江省\"钱江人才\"计划；浙江省高等学校中青年学科带头人；英国诺丁汉大学博士（PhD, University of Nottingham, UK）。SCI 期刊 ",{"type":19,"tag":27,"props":28,"children":29},"em",{},[30],{"type":24,"value":31},"EJOR",{"type":24,"value":33},"、",{"type":19,"tag":27,"props":35,"children":36},{},[37],{"type":24,"value":38},"TEVC",{"type":24,"value":33},{"type":19,"tag":27,"props":41,"children":42},{},[43],{"type":24,"value":44},"Networks",{"type":24,"value":46}," 编委。高质量学术论文 110 余篇，包括 ",{"type":19,"tag":27,"props":48,"children":49},{},[50],{"type":24,"value":51},"TRB",{"type":24,"value":33},{"type":19,"tag":27,"props":54,"children":55},{},[56],{"type":24,"value":57},"INFORMS JOC",{"type":24,"value":59}," 等 A 类期刊；主持国家自然基金及省市项目 20 余项，科研经费 1400 余万元；培养博士生 10 余名。",{"title":7,"searchDepth":61,"depth":61,"links":62},2,[],"markdown","content:members:staff:ruibin-bai.zh-CN.md","content","members\u002Fstaff\u002Fruibin-bai.zh-CN.md","members\u002Fstaff\u002Fruibin-bai","md","en","assets\u002F38.png","0000-0003-1722-568X",1,[74,84,93,99,110,120,126,136,145,153,161,168,175,182,189,199,207,216,224,235,242,251,259,267,275,284,292,306,313,320,328,338,346,355,364,372,378,384,392,399,407,415,425,432,438,447,454,461,467,474,485,492,500,506,516,523,529,537,545,553,560,568,574,584,593,602,609,621,629,635,641,648,653,663,670,678,687,695,701,708,716,722,729,737,743,751,757,763,770,781,789,796,803,811,819,825,832,840,849,856,864,871,878,892,900,906,915,924,937,946,952,962,968,975,982,989,995,1001,1010,1016,1022,1031,1043,1051,1059,1069,1079,1090,1098,1107,1114,1121,1129,1139,1148,1155,1162,1171,1179,1187],{"_path":75,"title":76,"authors":77,"year":80,"doi":81,"venue":82,"_id":83},"\u002Fpublications\u002F2007\u002Fa-model-for-fresh-produce-shelf-space-allocation-and-inventory-management-with-f","A Model for Fresh Produce Shelf-Space Allocation and Inventory Management with Freshness-Condition-Dependent Demand",[78,79],"Bai, Ruibin","Kendall, Graham",2007,"https:\u002F\u002Fdoi.org\u002F10.1287\u002Fijoc.1070.0219","INFORMS journal on computing","content:publications:2007:a-model-for-fresh-produce-shelf-space-allocation-and-inventory-management-with-f.md",{"_path":85,"title":86,"authors":87,"year":89,"doi":90,"venue":91,"_id":92},"\u002Fpublications\u002F2009\u002Fcanonical-representation-genetic-programming","Canonical representation genetic programming",[88,78],"Woodward, John R.",2009,"https:\u002F\u002Fdoi.org\u002F10.1145\u002F1543834.1543914",null,"content:publications:2009:canonical-representation-genetic-programming.md",{"_path":94,"title":95,"authors":96,"year":89,"doi":97,"venue":91,"_id":98},"\u002Fpublications\u002F2009\u002Fwhy-evolution-is-not-a-good-paradigm-for-program-induction","Why evolution is not a good paradigm for program induction",[88,78],"https:\u002F\u002Fdoi.org\u002F10.1145\u002F1543834.1543915","content:publications:2009:why-evolution-is-not-a-good-paradigm-for-program-induction.md",{"_path":100,"title":101,"authors":102,"year":107,"doi":108,"venue":91,"_id":109},"\u002Fpublications\u002F2010\u002Fa-decision-support-approach-for-group-decision-making-under-risk-and-uncertainty","A decision support approach for group decision making under risk and uncertainty",[103,79,104,105,106,78],"Li, Jiawei","Pollard, Simon","Soane, Emma","Davies, Gareth",2010,"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ficlsim.2010.5461315","content:publications:2010:a-decision-support-approach-for-group-decision-making-under-risk-and-uncertainty.md",{"_path":111,"title":112,"authors":113,"year":107,"doi":117,"venue":118,"_id":119},"\u002Fpublications\u002F2010\u002Fa-hybrid-evolutionary-approach-to-the-nurse-rostering-problem","A Hybrid Evolutionary Approach to the Nurse Rostering Problem",[78,114,79,115,116],"Burke, Edmund","Li, Jingpeng","McCollum, Barry","https:\u002F\u002Fdoi.org\u002F10.1109\u002Ftevc.2009.2033583","IEEE Transactions on Evolutionary Computation","content:publications:2010:a-hybrid-evolutionary-approach-to-the-nurse-rostering-problem.md",{"_path":121,"title":122,"authors":123,"year":107,"doi":124,"venue":91,"_id":125},"\u002Fpublications\u002F2010\u002Fan-efficient-guided-local-search-approach-for-service-network-design-problem-wit","An efficient guided local search approach for service network design problem with asset balancing",[78,79,103],"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ficlsim.2010.5461456","content:publications:2010:an-efficient-guided-local-search-approach-for-service-network-design-problem-wit.md",{"_path":127,"title":128,"authors":129,"year":132,"doi":133,"venue":134,"_id":135},"\u002Fpublications\u002F2011\u002Ftabu-assisted-guided-local-search-approaches-for-freight-service-network-design","Tabu assisted guided local search approaches for freight service network design",[78,79,130,131],"Qu, Rong","Atkin, Jason",2011,"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.ins.2011.11.028","Information Sciences","content:publications:2011:tabu-assisted-guided-local-search-approaches-for-freight-service-network-design.md",{"_path":137,"title":138,"authors":139,"year":141,"doi":142,"venue":143,"_id":144},"\u002Fpublications\u002F2012\u002Fa-new-model-and-a-hyper-heuristic-approach-for-two-dimensional-shelf-space-alloc","A new model and a hyper-heuristic approach for two-dimensional shelf space allocation",[78,140,79,114],"Woensel, Tom Van",2012,"https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10288-012-0211-2","4OR","content:publications:2012:a-new-model-and-a-hyper-heuristic-approach-for-two-dimensional-shelf-space-alloc.md",{"_path":146,"title":147,"authors":148,"year":141,"doi":150,"venue":151,"_id":152},"\u002Fpublications\u002F2012\u002Fevidence-and-belief-in-regulatory-decisions-incorporating-expected-utility-into","Evidence and belief in regulatory decisions – Incorporating expected utility into decision modelling",[103,106,79,105,78,149,104],"Rocks, Sophie A.","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.eswa.2012.01.193","Expert Systems with Applications","content:publications:2012:evidence-and-belief-in-regulatory-decisions-incorporating-expected-utility-into.md",{"_path":154,"title":155,"authors":156,"year":157,"doi":158,"venue":159,"_id":160},"\u002Fpublications\u002F2013\u002Fa-novel-approach-to-independent-taxi-scheduling-problem-based-on-stable-matching","A novel approach to independent taxi scheduling problem based on stable matching",[78,103,131,79],2013,"https:\u002F\u002Fdoi.org\u002F10.1057\u002Fjors.2013.96","Journal of the Operational Research Society","content:publications:2013:a-novel-approach-to-independent-taxi-scheduling-problem-based-on-stable-matching.md",{"_path":162,"title":163,"authors":164,"year":157,"doi":166,"venue":159,"_id":167},"\u002Fpublications\u002F2013\u002Fa-path-oriented-encoding-evolutionary-algorithm-for-network-coding-resource-mini","A path-oriented encoding evolutionary algorithm for network coding resource minimization",[165,130,79,78],"Xing, Huanlai","https:\u002F\u002Fdoi.org\u002F10.1057\u002Fjors.2013.79","content:publications:2013:a-path-oriented-encoding-evolutionary-algorithm-for-network-coding-resource-mini.md",{"_path":169,"title":170,"authors":171,"year":157,"doi":91,"venue":91,"_id":174},"\u002Fpublications\u002F2013\u002Fa-study-of-node-based-large-neighbourhood-approaches-for-the-logistics-service-n","A Study of Node Based Large Neighbourhood Approaches for the Logistics Service Network Optimisation",[78,172,173,88],"Hong-hua, Gan","Bei, Yijun","content:publications:2013:a-study-of-node-based-large-neighbourhood-approaches-for-the-logistics-service-n.md",{"_path":176,"title":177,"authors":178,"year":157,"doi":180,"venue":91,"_id":181},"\u002Fpublications\u002F2013\u002Fa-task-based-approach-for-a-real-world-commodity-routing-problem","A task based approach for a real-world commodity routing problem",[179,78,130,79],"Chen, Jianjun","https:\u002F\u002Fdoi.org\u002F10.1109\u002Fcipls.2013.6595193","content:publications:2013:a-task-based-approach-for-a-real-world-commodity-routing-problem.md",{"_path":183,"title":184,"authors":185,"year":157,"doi":187,"venue":151,"_id":188},"\u002Fpublications\u002F2013\u002Fpredicting-open-ios-adoption-in-smes-an-integrated-sem-neural-network-approach","Predicting open IOS adoption in SMEs: An integrated SEM-neural network approach",[186,78],"Chong, Alain Yee‐Loong","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.eswa.2013.07.023","content:publications:2013:predicting-open-ios-adoption-in-smes-an-integrated-sem-neural-network-approach.md",{"_path":190,"title":191,"authors":192,"year":157,"doi":196,"venue":197,"_id":198},"\u002Fpublications\u002F2013\u002Fswarm-intelligence-in-big-data-analytics","Swarm Intelligence in Big Data Analytics",[193,194,195,78],"Cheng, Shi","Shi, Yuhui","Qin, Quande","https:\u002F\u002Fdoi.org\u002F10.1007\u002F978-3-642-41278-3_51","Lecture notes in computer science","content:publications:2013:swarm-intelligence-in-big-data-analytics.md",{"_path":200,"title":201,"authors":202,"year":204,"doi":205,"venue":91,"_id":206},"\u002Fpublications\u002F2014\u002Fa-combinatorial-algorithm-for-the-cardinality-constrained-portfolio-optimization","A combinatorial algorithm for the cardinality constrained portfolio optimization problem",[203,193,78],"Cui, Tianxiang",2014,"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fcec.2014.6900357","content:publications:2014:a-combinatorial-algorithm-for-the-cardinality-constrained-portfolio-optimization.md",{"_path":208,"title":209,"authors":210,"year":204,"doi":213,"venue":214,"_id":215},"\u002Fpublications\u002F2014\u002Fa-strategic-approach-to-improve-sustainability-in-transportation-service-procure","A strategic approach to improve sustainability in transportation service procurement",[211,78,212],"Basu, R. Jothi","Palaniappan, PL.K.","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.tre.2014.10.015","Transportation Research Part E Logistics and Transportation Review","content:publications:2014:a-strategic-approach-to-improve-sustainability-in-transportation-service-procure.md",{"_path":217,"title":218,"authors":219,"year":204,"doi":221,"venue":222,"_id":223},"\u002Fpublications\u002F2014\u002Fhybridising-heuristics-within-an-estimation-distribution-algorithm-for-examinati","Hybridising heuristics within an estimation distribution algorithm for examination timetabling",[130,220,78,79],"Pham, Nam Ngoc","https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10489-014-0615-0","Applied Intelligence","content:publications:2014:hybridising-heuristics-within-an-estimation-distribution-algorithm-for-examinati.md",{"_path":225,"title":226,"authors":227,"year":204,"doi":232,"venue":233,"_id":234},"\u002Fpublications\u002F2014\u002Flife-cycle-resource-consumption-of-automotive-power-seats","Life cycle resource consumption of automotive power seats",[228,229,230,231,78],"Chen, Yisong","Yang, Yanping","Li, Xiang","Dong, Haibo","https:\u002F\u002Fdoi.org\u002F10.1080\u002F00207233.2014.942150","International Journal of Environmental Studies","content:publications:2014:life-cycle-resource-consumption-of-automotive-power-seats.md",{"_path":236,"title":237,"authors":238,"year":204,"doi":240,"venue":91,"_id":241},"\u002Fpublications\u002F2014\u002Fmaintaining-population-diversity-in-brain-storm-optimization-algorithm","Maintaining population diversity in brain storm optimization algorithm",[193,194,195,239,78],"Ting, T. O.","https:\u002F\u002Fdoi.org\u002F10.1109\u002Fcec.2014.6900255","content:publications:2014:maintaining-population-diversity-in-brain-storm-optimization-algorithm.md",{"_path":243,"title":244,"authors":245,"year":204,"doi":249,"venue":91,"_id":250},"\u002Fpublications\u002F2014\u002Fmodeling-urban-road-risky-driving-behaviors-in-china-with-multi-agent-microscopi","Modeling urban road risky driving behaviors in China with multi-agent microscopic traffic simulation",[246,78,247,248],"Li, Xia","Siebers, Peer‐Olaf","Wagner, Christian","https:\u002F\u002Fdoi.org\u002F10.1109\u002Fitsc.2014.6957944","content:publications:2014:modeling-urban-road-risky-driving-behaviors-in-china-with-multi-agent-microscopi.md",{"_path":252,"title":253,"authors":254,"year":204,"doi":256,"venue":257,"_id":258},"\u002Fpublications\u002F2014\u002Fpopulation-diversity-maintenance-in-brain-storm-optimization-algorithm","Population Diversity Maintenance In Brain Storm Optimization Algorithm",[193,194,195,255,78],"Zhang, Qingyu","https:\u002F\u002Fdoi.org\u002F10.1515\u002Fjaiscr-2015-0001","Journal of Artificial Intelligence and Soft Computing Research","content:publications:2014:population-diversity-maintenance-in-brain-storm-optimization-algorithm.md",{"_path":260,"title":261,"authors":262,"year":204,"doi":264,"venue":265,"_id":266},"\u002Fpublications\u002F2014\u002Fsearch-with-evolutionary-ruin-and-stochastic-rebuild-a-theoretic-framework-and-a","Search with evolutionary ruin and stochastic rebuild: A theoretic framework and a case study on exam timetabling",[115,78,263,130],"Shen, Yindong","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.ejor.2014.11.002","European Journal of Operational Research","content:publications:2014:search-with-evolutionary-ruin-and-stochastic-rebuild-a-theoretic-framework-and-a.md",{"_path":268,"title":269,"authors":270,"year":204,"doi":272,"venue":273,"_id":274},"\u002Fpublications\u002F2014\u002Fstochastic-service-network-design-with-rerouting","Stochastic service network design with rerouting",[78,271,115,186],"Wallace, Stein W.","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.trb.2013.11.001","Transportation Research Part B Methodological","content:publications:2014:stochastic-service-network-design-with-rerouting.md",{"_path":276,"title":277,"authors":278,"year":281,"doi":282,"venue":91,"_id":283},"\u002Fpublications\u002F2015\u002Fa-hybrid-genetic-algorithm-for-a-two-stage-stochastic-portfolio-optimization-wit","A hybrid genetic algorithm for a two-stage stochastic portfolio optimization with uncertain asset prices",[203,78,279,280,130,115],"Parkes, Andrew J.","He, Fang",2015,"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fcec.2015.7257198","content:publications:2015:a-hybrid-genetic-algorithm-for-a-two-stage-stochastic-portfolio-optimization-wit.md",{"_path":285,"title":286,"authors":287,"year":281,"doi":290,"venue":273,"_id":291},"\u002Fpublications\u002F2015\u002Fa-set-covering-model-for-a-bidirectional-multi-shift-full-truckload-vehicle-rout","A set-covering model for a bidirectional multi-shift full truckload vehicle routing problem",[78,288,179,289],"Xue, Ning","Roberts, Gethin Wyn","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.trb.2015.06.002","content:publications:2015:a-set-covering-model-for-a-bidirectional-multi-shift-full-truckload-vehicle-rout.md",{"_path":293,"title":294,"authors":295,"year":281,"doi":304,"venue":159,"_id":305},"\u002Fpublications\u002F2015\u002Fgood-laboratory-practice-for-optimization-research","Good Laboratory Practice for optimization research",[79,78,296,297,298,299,103,116,300,130,301,302,303],"Błażewicz, Jacek","Causmaecker, Patrick De","Gendreau, Michel","John, Robert","Pesch, Erwin","Sabar, Nasser R.","Berghe, Greet Vanden","Yee, Angelina Seow Voon","https:\u002F\u002Fdoi.org\u002F10.1057\u002Fjors.2015.77","content:publications:2015:good-laboratory-practice-for-optimization-research.md",{"_path":307,"title":308,"authors":309,"year":310,"doi":311,"venue":91,"_id":312},"\u002Fpublications\u002F2016\u002Fa-dynamic-truck-dispatching-problem-in-marine-container-terminal","A dynamic truck dispatching problem in marine container terminal",[179,78,231,130,79],2016,"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fssci.2016.7850081","content:publications:2016:a-dynamic-truck-dispatching-problem-in-marine-container-terminal.md",{"_path":314,"title":315,"authors":316,"year":310,"doi":318,"venue":91,"_id":319},"\u002Fpublications\u002F2016\u002Fa-new-fast-large-neighbourhood-search-for-service-network-design-with-asset-bala","A new fast large neighbourhood search for service network design with asset balance constraints",[78,88,317],"Subramanian, Nachiappan","https:\u002F\u002Fdoi.org\u002F10.1109\u002Fssci.2016.7850084","content:publications:2016:a-new-fast-large-neighbourhood-search-for-service-network-design-with-asset-bala.md",{"_path":321,"title":322,"authors":323,"year":310,"doi":325,"venue":326,"_id":327},"\u002Fpublications\u002F2016\u002Fa-scheme-for-determining-vehicle-routes-based-on-arc-based-service-network-desig","A scheme for determining vehicle routes based on Arc-based service network design",[324,78,131,79],"Jiang, Xiaoping","https:\u002F\u002Fdoi.org\u002F10.1080\u002F03155986.2016.1262580","INFOR Information Systems and Operational Research","content:publications:2016:a-scheme-for-determining-vehicle-routes-based-on-arc-based-service-network-desig.md",{"_path":329,"title":330,"authors":331,"year":310,"doi":335,"venue":336,"_id":337},"\u002Fpublications\u002F2016\u002Fa-theoretical-and-empirical-integrated-method-to-select-the-optimal-combined-sig","A Theoretical and Empirical Integrated Method to Select the Optimal Combined Signals for Geometry-Free and Geometry-Based Three-Carrier Ambiguity Resolution",[332,289,333,334,78],"Zhao, Dongsheng","Lau, Lawrence","Hancock, Craig","https:\u002F\u002Fdoi.org\u002F10.3390\u002Fs16111929","Sensors","content:publications:2016:a-theoretical-and-empirical-integrated-method-to-select-the-optimal-combined-sig.md",{"_path":339,"title":340,"authors":341,"year":310,"doi":344,"venue":91,"_id":345},"\u002Fpublications\u002F2016\u002Fa-variable-neighbourhood-search-algorithm-with-compound-neighbourhoods-for-vrptw","A Variable Neighbourhood Search Algorithm with Compound Neighbourhoods for VRPTW",[342,130,78,343],"Chen, Binhui","Ishibuchi, Hisao","https:\u002F\u002Fdoi.org\u002F10.5220\u002F0005661800250035","content:publications:2016:a-variable-neighbourhood-search-algorithm-with-compound-neighbourhoods-for-vrptw.md",{"_path":347,"title":348,"authors":349,"year":310,"doi":352,"venue":353,"_id":354},"\u002Fpublications\u002F2016\u002Fcold-chain-configuration-design-location-allocation-decision-making-using-coordi","Cold chain configuration design: location-allocation decision-making using coordination, value deterioration, and big data approximation",[350,317,351,78],"Singh, Adarsh Kumar","Pawar, Kulwant S.","https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10479-016-2332-z","Annals of Operations Research","content:publications:2016:cold-chain-configuration-design-location-allocation-decision-making-using-coordi.md",{"_path":356,"title":357,"authors":358,"year":310,"doi":91,"venue":362,"_id":363},"\u002Fpublications\u002F2016\u002Fdevelopment-of-a-framework-for-big-data-analytics-in-cold-chain-logistics","Development of a framework for big data analytics in cold chain logistics",[359,360,361,317,78,351],"Chaudhuri, Atanu","Dukovska‐Popovska, Iskra","Chan, Hing Kai","VBN Forskningsportal (Aalborg Universitet)","content:publications:2016:development-of-a-framework-for-big-data-analytics-in-cold-chain-logistics.md",{"_path":365,"title":366,"authors":367,"year":310,"doi":369,"venue":370,"_id":371},"\u002Fpublications\u002F2016\u002Fenvironmental-and-financial-performance-of-mechanical-recycling-of-carbon-fibre","Environmental and financial performance of mechanical recycling of carbon fibre reinforced polymers and comparison with conventional disposal routes",[230,78,368],"McKechnie, Jon","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.jclepro.2016.03.139","Journal of Cleaner Production","content:publications:2016:environmental-and-financial-performance-of-mechanical-recycling-of-carbon-fibre.md",{"_path":373,"title":374,"authors":375,"year":310,"doi":376,"venue":91,"_id":377},"\u002Fpublications\u002F2016\u002Ffreight-vehicle-travel-time-prediction-using-gradient-boosting-regression-tree","Freight Vehicle Travel Time Prediction Using Gradient Boosting Regression Tree",[246,78],"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ficmla.2016.0182","content:publications:2016:freight-vehicle-travel-time-prediction-using-gradient-boosting-regression-tree.md",{"_path":379,"title":380,"authors":381,"year":310,"doi":382,"venue":197,"_id":383},"\u002Fpublications\u002F2016\u002Ffreight-vehicle-travel-time-prediction-using-sparse-gaussian-processes-regressio","Freight Vehicle Travel Time Prediction Using Sparse Gaussian Processes Regression with Trajectory Data",[246,78],"https:\u002F\u002Fdoi.org\u002F10.1007\u002F978-3-319-46257-8_16","content:publications:2016:freight-vehicle-travel-time-prediction-using-sparse-gaussian-processes-regressio.md",{"_path":385,"title":386,"authors":387,"year":388,"doi":389,"venue":390,"_id":391},"\u002Fpublications\u002F2017\u002Fan-investigation-on-compound-neighborhoods-for-vrptw","An Investigation on Compound Neighborhoods for VRPTW",[342,130,78,343],2017,"https:\u002F\u002Fdoi.org\u002F10.1007\u002F978-3-319-53982-9_1","Communications in computer and information science","content:publications:2017:an-investigation-on-compound-neighborhoods-for-vrptw.md",{"_path":393,"title":394,"authors":395,"year":388,"doi":396,"venue":397,"_id":398},"\u002Fpublications\u002F2017\u002Fcycle-slip-detection-for-triple-frequency-gps-observations-under-ionospheric-sci","Cycle-slip Detection for Triple-frequency GPS Observations Under Ionospheric Scintillation",[332,289,334,333,78],"https:\u002F\u002Fdoi.org\u002F10.33012\u002F2017.15326","Proceedings of the Satellite Division's International Technical Meeting (Online)\u002FProceedings of the Satellite Division's International Technical Meeting (CD-ROM)","content:publications:2017:cycle-slip-detection-for-triple-frequency-gps-observations-under-ionospheric-sci.md",{"_path":400,"title":401,"authors":402,"year":388,"doi":404,"venue":405,"_id":406},"\u002Fpublications\u002F2017\u002Foptimisation-of-transportation-service-network-using-k-node-large-neighbourhood","Optimisation of transportation service network using κ -node large neighbourhood search",[78,88,317,403],"Cartlidge, John","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.cor.2017.06.008","Computers & Operations Research","content:publications:2017:optimisation-of-transportation-service-network-using-κ-node-large-neighbourhood.md",{"_path":408,"title":409,"authors":410,"year":412,"doi":413,"venue":222,"_id":414},"\u002Fpublications\u002F2018\u002Fa-hyper-heuristic-with-two-guidance-indicators-for-bi-objective-mixed-shift-vehi","A hyper-heuristic with two guidance indicators for bi-objective mixed-shift vehicle routing problem with time windows",[342,130,78,411],"Laesanklang, Wasakorn",2018,"https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10489-018-1250-y","content:publications:2018:a-hyper-heuristic-with-two-guidance-indicators-for-bi-objective-mixed-shift-vehi.md",{"_path":416,"title":417,"authors":418,"year":412,"doi":423,"venue":91,"_id":424},"\u002Fpublications\u002F2018\u002Fautomated-prediction-of-shopping-behaviours-using-taxi-trajectory-data-and-socia","Automated prediction of shopping behaviours using taxi trajectory data and social media reviews",[419,403,78,420,421,422],"Gong, Shuhui","Yue, Yang","Li, Qingquan","Qiu, Guoping","https:\u002F\u002Fdoi.org\u002F10.1109\u002Ficbda.2018.8367661","content:publications:2018:automated-prediction-of-shopping-behaviours-using-taxi-trajectory-data-and-socia.md",{"_path":426,"title":427,"authors":428,"year":412,"doi":429,"venue":430,"_id":431},"\u002Fpublications\u002F2018\u002Fdecision-making-in-cold-chain-logistics-using-data-analytics-a-literature-review","Decision-making in cold chain logistics using data analytics: a literature review",[359,360,317,361,78],"https:\u002F\u002Fdoi.org\u002F10.1108\u002Fijlm-03-2017-0059","The International Journal of Logistics Management","content:publications:2018:decision-making-in-cold-chain-logistics-using-data-analytics-a-literature-review.md",{"_path":433,"title":434,"authors":435,"year":412,"doi":436,"venue":91,"_id":437},"\u002Fpublications\u002F2018\u002Fspatio-temporal-prediction-of-shopping-behaviours-using-taxi-trajectory-data","Spatio-temporal prediction of shopping behaviours using taxi trajectory data",[403,419,78,420,421,422],"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ficbda.2018.8367660","content:publications:2018:spatio-temporal-prediction-of-shopping-behaviours-using-taxi-trajectory-data.md",{"_path":439,"title":440,"authors":441,"year":443,"doi":444,"venue":445,"_id":446},"\u002Fpublications\u002F2019\u002Fa-hybrid-combinatorial-approach-to-a-two-stage-stochastic-portfolio-optimization","A hybrid combinatorial approach to a two-stage stochastic portfolio optimization model with uncertain asset prices",[203,78,442,279,130,280,115],"Ding, Shusheng",2019,"https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs00500-019-04517-y","Soft Computing","content:publications:2019:a-hybrid-combinatorial-approach-to-a-two-stage-stochastic-portfolio-optimization.md",{"_path":448,"title":449,"authors":450,"year":443,"doi":451,"venue":452,"_id":453},"\u002Fpublications\u002F2019\u002Fa-triple-frequency-cycle-slip-detection-and-correction-method-based-on-modified","A triple-frequency cycle slip detection and correction method based on modified HMW combinations applied on GPS and BDS",[332,289,334,333,78],"https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10291-018-0817-8","GPS Solutions","content:publications:2019:a-triple-frequency-cycle-slip-detection-and-correction-method-based-on-modified.md",{"_path":455,"title":456,"authors":457,"year":443,"doi":458,"venue":459,"_id":460},"\u002Fpublications\u002F2019\u002Fa-variable-neighborhood-search-algorithm-with-reinforcement-learning-for-a-real","A variable neighborhood search algorithm with reinforcement learning for a real-life periodic vehicle routing problem with time windows and open routes",[342,130,78,411],"https:\u002F\u002Fdoi.org\u002F10.1051\u002Fro\u002F2019080","RAIRO - Operations Research","content:publications:2019:a-variable-neighborhood-search-algorithm-with-reinforcement-learning-for-a-real.md",{"_path":462,"title":463,"authors":464,"year":443,"doi":465,"venue":91,"_id":466},"\u002Fpublications\u002F2019\u002Factivity-modelling-using-journey-pairing-of-taxi-trajectory-data","Activity Modelling Using Journey Pairing of Taxi Trajectory Data",[419,403,78,420,421,422],"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ficbda.2019.8712832","content:publications:2019:activity-modelling-using-journey-pairing-of-taxi-trajectory-data.md",{"_path":468,"title":469,"authors":470,"year":443,"doi":471,"venue":472,"_id":473},"\u002Fpublications\u002F2019\u002Fextracting-activity-patterns-from-taxi-trajectory-data-a-two-layer-framework-usi","Extracting activity patterns from taxi trajectory data: a two-layer framework using spatio-temporal clustering, Bayesian probability and Monte Carlo simulation",[419,403,78,420,421,422],"https:\u002F\u002Fdoi.org\u002F10.1080\u002F13658816.2019.1641715","International Journal of Geographical Information Systems","content:publications:2019:extracting-activity-patterns-from-taxi-trajectory-data-a-two-layer-framework-usi.md",{"_path":475,"title":476,"authors":477,"year":443,"doi":482,"venue":483,"_id":484},"\u002Fpublications\u002F2019\u002Fregular-expression-based-medical-text-classification-using-constructive-heuristi","Regular Expression Based Medical Text Classification Using Constructive Heuristic Approach",[478,78,479,230,480,481],"Cui, Menglin","Lu, Zheng","Aickelin, Uwe","Ge, Peiming","https:\u002F\u002Fdoi.org\u002F10.1109\u002Faccess.2019.2946622","IEEE Access","content:publications:2019:regular-expression-based-medical-text-classification-using-constructive-heuristi.md",{"_path":486,"title":487,"authors":488,"year":443,"doi":489,"venue":490,"_id":491},"\u002Fpublications\u002F2019\u002Ftravel-time-prediction-in-transport-and-logistics","Travel time prediction in transport and logistics",[246,78,247,248],"https:\u002F\u002Fdoi.org\u002F10.1108\u002Fvjikms-11-2018-0102","VINE Journal of Information and Knowledge Management Systems","content:publications:2019:travel-time-prediction-in-transport-and-logistics.md",{"_path":493,"title":494,"authors":495,"year":497,"doi":498,"venue":91,"_id":499},"\u002Fpublications\u002F2020\u002Fa-data-driven-genetic-programming-heuristic-for-real-world-dynamic-seaport-conta","A Data-Driven Genetic Programming Heuristic for Real-World Dynamic Seaport Container Terminal Truck Dispatching",[496,78,130,231,179],"Chen, Xinan",2020,"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fcec48606.2020.9185659","content:publications:2020:a-data-driven-genetic-programming-heuristic-for-real-world-dynamic-seaport-conta.md",{"_path":501,"title":502,"authors":503,"year":497,"doi":504,"venue":265,"_id":505},"\u002Fpublications\u002F2020\u002Fa-hybrid-pricing-and-cutting-approach-for-the-multi-shift-full-truckload-vehicle","A hybrid pricing and cutting approach for the multi-shift full truckload vehicle routing problem",[288,78,130,480],"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.ejor.2020.10.037","content:publications:2020:a-hybrid-pricing-and-cutting-approach-for-the-multi-shift-full-truckload-vehicle.md",{"_path":507,"title":508,"authors":509,"year":497,"doi":513,"venue":514,"_id":515},"\u002Fpublications\u002F2020\u002Fa-multiobjective-single-bus-corridor-scheduling-using-machine-learning-based-pre","A multiobjective single bus corridor scheduling using machine learning-based predictive models",[510,78,103,511,288,512],"Chen, Bing","Liu, Yueni","Ren, Jianfeng","https:\u002F\u002Fdoi.org\u002F10.1080\u002F00207543.2020.1766716","International Journal of Production Research","content:publications:2020:a-multiobjective-single-bus-corridor-scheduling-using-machine-learning-based-pre.md",{"_path":517,"title":518,"authors":519,"year":497,"doi":521,"venue":483,"_id":522},"\u002Fpublications\u002F2020\u002Fa-regularized-attribute-weighting-framework-for-naive-bayes","A Regularized Attribute Weighting Framework for Naive Bayes",[520,512,78],"Wang, Shihe","https:\u002F\u002Fdoi.org\u002F10.1109\u002Faccess.2020.3044946","content:publications:2020:a-regularized-attribute-weighting-framework-for-naive-bayes.md",{"_path":524,"title":525,"authors":526,"year":497,"doi":527,"venue":91,"_id":528},"\u002Fpublications\u002F2020\u002Fdata-driven-agent-based-model-of-intra-urban-activities","Data-Driven Agent-Based Model of Intra-Urban Activities",[419,403,78,420,421,422],"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ficbda49040.2020.9101327","content:publications:2020:data-driven-agent-based-model-of-intra-urban-activities.md",{"_path":530,"title":531,"authors":532,"year":497,"doi":535,"venue":91,"_id":536},"\u002Fpublications\u002F2020\u002Fdata-driven-regular-expressions-evolution-for-medical-text-classification-using","Data-Driven Regular Expressions Evolution for Medical Text Classification Using Genetic Programming",[533,78,479,481,480,534],"Liu, Jiandong","Liu, Daoyun","https:\u002F\u002Fdoi.org\u002F10.1109\u002Fcec48606.2020.9185500","content:publications:2020:data-driven-regular-expressions-evolution-for-medical-text-classification-using.md",{"_path":538,"title":539,"authors":540,"year":497,"doi":542,"venue":543,"_id":544},"\u002Fpublications\u002F2020\u002Fforecasting-stock-market-return-with-nonlinearity-a-genetic-programming-approach","Forecasting stock market return with nonlinearity: a genetic programming approach",[442,203,541,78],"Xiong, Xihan","https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs12652-020-01762-0","Journal of Ambient Intelligence and Humanized Computing","content:publications:2020:forecasting-stock-market-return-with-nonlinearity-a-genetic-programming-approach.md",{"_path":546,"title":547,"authors":548,"year":497,"doi":550,"venue":551,"_id":552},"\u002Fpublications\u002F2020\u002Ffuzzy-c-means-based-scenario-bundling-for-stochastic-service-network-design","Fuzzy C-means-based scenario bundling for stochastic service network design",[324,78,549,480],"Landa-Silva, Dario","https:\u002F\u002Fdoi.org\u002F10.48550\u002Farxiv.2011.09890","arXiv (Cornell University)","content:publications:2020:fuzzy-c-means-based-scenario-bundling-for-stochastic-service-network-design.md",{"_path":554,"title":555,"authors":556,"year":497,"doi":557,"venue":558,"_id":559},"\u002Fpublications\u002F2020\u002Fgeographical-and-temporal-huff-model-calibration-using-taxi-trajectory-data","Geographical and temporal huff model calibration using taxi trajectory data",[419,403,78,420,421,422],"https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10707-019-00390-x","GeoInformatica","content:publications:2020:geographical-and-temporal-huff-model-calibration-using-taxi-trajectory-data.md",{"_path":561,"title":562,"authors":563,"year":497,"doi":566,"venue":551,"_id":567},"\u002Fpublications\u002F2020\u002Fretrieving-and-ranking-short-medical-questions-with-two-stages-neural-matching-m","Retrieving and ranking short medical questions with two stages neural matching model",[230,564,479,78,480,481,565],"Fu, Xinyu","Liu, Gong","https:\u002F\u002Fdoi.org\u002F10.48550\u002Farxiv.2012.01254","content:publications:2020:retrieving-and-ranking-short-medical-questions-with-two-stages-neural-matching-m.md",{"_path":569,"title":570,"authors":571,"year":497,"doi":572,"venue":405,"_id":573},"\u002Fpublications\u002F2020\u002Fsoft-clustering-based-scenario-bundling-for-a-progressive-hedging-heuristic-in-s","Soft clustering-based scenario bundling for a progressive hedging heuristic in stochastic service network design",[324,78,271,79,549],"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.cor.2020.105182","content:publications:2020:soft-clustering-based-scenario-bundling-for-a-progressive-hedging-heuristic-in-s.md",{"_path":575,"title":576,"authors":577,"year":581,"doi":582,"venue":265,"_id":583},"\u002Fpublications\u002F2021\u002Fa-deep-reinforcement-learning-based-hyper-heuristic-for-combinatorial-optimisati","A deep reinforcement learning based hyper-heuristic for combinatorial optimisation with uncertainties",[578,78,130,579,580],"Zhang, Yuchang","Tu, Chaofan","Jin, Jiahuan",2021,"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.ejor.2021.10.032","content:publications:2021:a-deep-reinforcement-learning-based-hyper-heuristic-for-combinatorial-optimisati.md",{"_path":585,"title":586,"authors":587,"year":581,"doi":590,"venue":591,"_id":592},"\u002Fpublications\u002F2021\u002Fa-fuzzy-based-heuristic-algorithm-for-online-outbound-container-stacking-problem","A Fuzzy-based Heuristic Algorithm for Online Outbound Container Stacking Problem with Uncertain Weight Information",[103,588,589,78],"Zhou, Can","Wu, Kejia","https:\u002F\u002Fdoi.org\u002F10.1109\u002Fssci50451.2021.9660070","2021 IEEE Symposium Series on Computational Intelligence (SSCI)","content:publications:2021:a-fuzzy-based-heuristic-algorithm-for-online-outbound-container-stacking-problem.md",{"_path":594,"title":595,"authors":596,"year":581,"doi":599,"venue":600,"_id":601},"\u002Fpublications\u002F2021\u002Fa-genetic-optimization-resampling-based-particle-filtering-algorithm-for-indoor","A Genetic Optimization Resampling Based Particle Filtering Algorithm for Indoor Target Tracking",[597,333,78,598],"Zhou, Ning","Moore, Terry","https:\u002F\u002Fdoi.org\u002F10.3390\u002Frs13010132","Remote Sensing","content:publications:2021:a-genetic-optimization-resampling-based-particle-filtering-algorithm-for-indoor.md",{"_path":603,"title":604,"authors":605,"year":581,"doi":606,"venue":607,"_id":608},"\u002Fpublications\u002F2021\u002Fa-hybrid-medical-text-classification-framework-integrating-attentive-rule-constr","A hybrid medical text classification framework: Integrating attentive rule construction and neural network",[230,478,115,78,479,480],"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.neucom.2021.02.069","Neurocomputing","content:publications:2021:a-hybrid-medical-text-classification-framework-integrating-attentive-rule-constr.md",{"_path":610,"title":611,"authors":612,"year":581,"doi":619,"venue":514,"_id":620},"\u002Fpublications\u002F2021\u002Fanalytics-and-machine-learning-in-vehicle-routing-research","Analytics and machine learning in vehicle routing research",[78,496,613,203,419,614,324,615,580,79,103,616,512,617,288,618],"Chen, Zhi‐Long","He, Wentao","Jin, Huan","Lu, Zheng Feng","Weng, Paul","Zhang, Huayan","https:\u002F\u002Fdoi.org\u002F10.1080\u002F00207543.2021.2013566","content:publications:2021:analytics-and-machine-learning-in-vehicle-routing-research.md",{"_path":622,"title":623,"authors":624,"year":581,"doi":626,"venue":627,"_id":628},"\u002Fpublications\u002F2021\u002Fcollective-strategies-with-a-master-slave-mechanism-dominate-in-spatial-iterated","Collective Strategies With a Master-Slave Mechanism Dominate in Spatial-Iterated Prisoner's Dilemma",[103,625,115,78],"Duncan, Robert O.","https:\u002F\u002Fdoi.org\u002F10.4018\u002Fijsir.2021100103","International Journal of Swarm Intelligence Research","content:publications:2021:collective-strategies-with-a-master-slave-mechanism-dominate-in-spatial-iterated.md",{"_path":630,"title":631,"authors":632,"year":581,"doi":633,"venue":551,"_id":634},"\u002Fpublications\u002F2021\u002Fdata-augmentation-by-morphological-mixup-for-solving-raven-s-progressive-matrice","Data augmentation by morphological mixup for solving Raven's Progressive Matrices",[614,512,78],"https:\u002F\u002Fdoi.org\u002F10.48550\u002Farxiv.2103.05222","content:publications:2021:data-augmentation-by-morphological-mixup-for-solving-raven-s-progressive-matrice.md",{"_path":636,"title":637,"authors":638,"year":581,"doi":639,"venue":91,"_id":640},"\u002Fpublications\u002F2021\u002Fevolutionary-inspired-strategy-for-particle-distribution-optimization-in-auxilia","Evolutionary-Inspired Strategy for Particle Distribution Optimization in Auxiliary Particle Filtering Algorithm Based Indoor Positioning",[597,333,78,598],"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fipin51156.2021.9662586","content:publications:2021:evolutionary-inspired-strategy-for-particle-distribution-optimization-in-auxilia.md",{"_path":642,"title":643,"authors":644,"year":581,"doi":645,"venue":646,"_id":647},"\u002Fpublications\u002F2021\u002Fnovel-prior-position-determination-approaches-in-particle-filter-for-ultra-wideb","Novel prior position determination approaches in particle filter for ultra wideband (UWB)‐based indoor positioning",[597,333,78,598],"https:\u002F\u002Fdoi.org\u002F10.1002\u002Fnavi.415","NAVIGATION Journal of the Institute of Navigation","content:publications:2021:novel-prior-position-determination-approaches-in-particle-filter-for-ultra-wideb.md",{"_path":649,"title":650,"authors":651,"year":581,"doi":91,"venue":551,"_id":652},"\u002Fpublications\u002F2021\u002Fone-shot-visual-reasoning-on-rpms-with-an-application-to-video-frame-prediction","One-shot Visual Reasoning on RPMs with an Application to Video Frame Prediction",[614,512,78],"content:publications:2021:one-shot-visual-reasoning-on-rpms-with-an-application-to-video-frame-prediction.md",{"_path":654,"title":655,"authors":656,"year":581,"doi":661,"venue":91,"_id":662},"\u002Fpublications\u002F2021\u002Frppg-based-spoofing-detection-for-face-mask-attack-using-efficientnet-on-weighte","rPPG-Based Spoofing Detection for Face Mask Attack using Efficientnet on Weighted Spatial-Temporal Representation",[657,520,658,614,659,512,78,660],"Yao, Chenglin","Zhang, Jialu","Du, Heshan","Liu, Jiang","https:\u002F\u002Fdoi.org\u002F10.1109\u002Ficip42928.2021.9506276","content:publications:2021:rppg-based-spoofing-detection-for-face-mask-attack-using-efficientnet-on-weighte.md",{"_path":664,"title":665,"authors":666,"year":667,"doi":668,"venue":646,"_id":669},"\u002Fpublications\u002F2022\u002Fa-robust-detection-and-optimization-approach-for-delayed-measurements-in-uwb-par","A Robust Detection and Optimization Approach for Delayed Measurements in UWB Particle-Filter-Based Indoor Positioning",[597,333,78,598],2022,"https:\u002F\u002Fdoi.org\u002F10.33012\u002Fnavi.514","content:publications:2022:a-robust-detection-and-optimization-approach-for-delayed-measurements-in-uwb-par.md",{"_path":671,"title":672,"authors":673,"year":667,"doi":675,"venue":676,"_id":677},"\u002Fpublications\u002F2022\u002Fan-improved-ant-colony-approach-for-the-competitive-traveling-salesmen-problem","An Improved Ant Colony Approach for the Competitive Traveling Salesmen Problem",[674,78,203,130,103],"Du, Xinyang","https:\u002F\u002Fdoi.org\u002F10.1109\u002Fcec55065.2022.9870414","2022 IEEE Congress on Evolutionary Computation (CEC)","content:publications:2022:an-improved-ant-colony-approach-for-the-competitive-traveling-salesmen-problem.md",{"_path":679,"title":680,"authors":681,"year":667,"doi":684,"venue":685,"_id":686},"\u002Fpublications\u002F2022\u002Fboosting-the-discriminant-power-of-naive-bayes","Boosting the Discriminant Power of Naive Bayes",[520,512,682,78,683],"Lian, Xiaoyu","Jiang, Xudong","https:\u002F\u002Fdoi.org\u002F10.1109\u002Ficpr56361.2022.9956358","2022 26th International Conference on Pattern Recognition (ICPR)","content:publications:2022:boosting-the-discriminant-power-of-naive-bayes.md",{"_path":688,"title":689,"authors":690,"year":667,"doi":692,"venue":693,"_id":694},"\u002Fpublications\u002F2022\u002Fcontainer-terminal-daily-gate-in-and-gate-out-forecasting-using-machine-learning","Container terminal daily gate in and gate out forecasting using machine learning methods",[580,691,615,203,78],"Ma, Mingyu","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.tranpol.2022.11.010","Transport Policy","content:publications:2022:container-terminal-daily-gate-in-and-gate-out-forecasting-using-machine-learning.md",{"_path":696,"title":697,"authors":698,"year":667,"doi":699,"venue":118,"_id":700},"\u002Fpublications\u002F2022\u002Fcooperative-double-layer-genetic-programming-hyper-heuristic-for-online-containe","Cooperative Double-Layer Genetic Programming Hyper-Heuristic for Online Container Terminal Truck Dispatching",[496,78,130,231],"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ftevc.2022.3209985","content:publications:2022:cooperative-double-layer-genetic-programming-hyper-heuristic-for-online-containe.md",{"_path":702,"title":703,"authors":704,"year":667,"doi":706,"venue":151,"_id":707},"\u002Fpublications\u002F2022\u002Fcross-document-attention-based-gated-fusion-network-for-automated-medical-licens","Cross-document attention-based gated fusion network for automated medical licensing exam",[533,512,479,614,478,705,78],"Zhang, Zibo","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.eswa.2022.117588","content:publications:2022:cross-document-attention-based-gated-fusion-network-for-automated-medical-licens.md",{"_path":709,"title":710,"authors":711,"year":667,"doi":713,"venue":714,"_id":715},"\u002Fpublications\u002F2022\u002Fidentify-patterns-in-online-bin-packing-problem-an-adaptive-pattern-based-algori","Identify Patterns in Online Bin Packing Problem: An Adaptive Pattern-Based Algorithm",[712,103,78,130,203,615],"Lin, Bingchen","https:\u002F\u002Fdoi.org\u002F10.3390\u002Fsym14071301","Symmetry","content:publications:2022:identify-patterns-in-online-bin-packing-problem-an-adaptive-pattern-based-algori.md",{"_path":717,"title":718,"authors":719,"year":667,"doi":720,"venue":265,"_id":721},"\u002Fpublications\u002F2022\u002Flagrange-dual-bound-computation-for-stochastic-service-network-design","Lagrange dual bound computation for stochastic service network design",[324,78,512,103,79],"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.ejor.2022.01.044","content:publications:2022:lagrange-dual-bound-computation-for-stochastic-service-network-design.md",{"_path":723,"title":724,"authors":725,"year":726,"doi":727,"venue":151,"_id":728},"\u002Fpublications\u002F2023\u002Fa-deep-reinforcement-learning-hyper-heuristic-with-feature-fusion-for-online-pac","A deep reinforcement learning hyper-heuristic with feature fusion for online packing problems",[579,78,480,578,659],2023,"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.eswa.2023.120568","content:publications:2023:a-deep-reinforcement-learning-hyper-heuristic-with-feature-fusion-for-online-pac.md",{"_path":730,"title":731,"authors":732,"year":726,"doi":734,"venue":735,"_id":736},"\u002Fpublications\u002F2023\u002Fa-max-relevance-min-divergence-criterion-for-data-discretization-with-applicatio","A Max-Relevance-Min-Divergence criterion for data discretization with applications on naive Bayes",[520,512,78,733,683],"Yao, Yuan","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.patcog.2023.110236","Pattern Recognition","content:publications:2023:a-max-relevance-min-divergence-criterion-for-data-discretization-with-applicatio.md",{"_path":738,"title":739,"authors":740,"year":726,"doi":741,"venue":151,"_id":742},"\u002Fpublications\u002F2023\u002Fa-semi-supervised-adaptive-discriminative-discretization-method-improving-discri","A semi-supervised adaptive discriminative discretization method improving discrimination power of regularized naive Bayes",[520,512,78],"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.eswa.2023.120094","content:publications:2023:a-semi-supervised-adaptive-discriminative-discretization-method-improving-discri.md",{"_path":744,"title":745,"authors":746,"year":726,"doi":749,"venue":91,"_id":750},"\u002Fpublications\u002F2023\u002Fa-simulation-hyper-heuristic-method-for-multi-floor-agv-delivery-services-in-hos","A Simulation Hyper-Heuristic Method for Multi-Floor AGV Delivery Services in Hospitals",[747,496,748,78],"Yuan, Haocheng","Zhu, Junsong","https:\u002F\u002Fdoi.org\u002F10.1109\u002Fssci52147.2023.10371983","content:publications:2023:a-simulation-hyper-heuristic-method-for-multi-floor-agv-delivery-services-in-hos.md",{"_path":752,"title":753,"authors":754,"year":726,"doi":755,"venue":514,"_id":756},"\u002Fpublications\u002F2023\u002Fanalytics-and-machine-learning-in-scheduling-and-routing-research","Analytics and machine learning in scheduling and routing research",[78,613,79],"https:\u002F\u002Fdoi.org\u002F10.1080\u002F00207543.2022.2131930","content:publications:2023:analytics-and-machine-learning-in-scheduling-and-routing-research.md",{"_path":758,"title":759,"authors":760,"year":726,"doi":761,"venue":265,"_id":762},"\u002Fpublications\u002F2023\u002Fcontainer-port-truck-dispatching-optimization-using-real2sim-based-deep-reinforc","Container port truck dispatching optimization using Real2Sim based deep reinforcement learning",[580,203,78,130],"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.ejor.2023.11.038","content:publications:2023:container-port-truck-dispatching-optimization-using-real2sim-based-deep-reinforc.md",{"_path":764,"title":765,"authors":766,"year":726,"doi":767,"venue":768,"_id":769},"\u002Fpublications\u002F2023\u002Fdata-augmentation-by-morphological-mixup-for-solving-raven-s-progressive-matrice","Data augmentation by morphological mixup for solving Raven’s progressive matrices",[614,512,78],"https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs00371-023-02930-x","The Visual Computer","content:publications:2023:data-augmentation-by-morphological-mixup-for-solving-raven-s-progressive-matrice.md",{"_path":771,"title":772,"authors":773,"year":726,"doi":779,"venue":197,"_id":780},"\u002Fpublications\u002F2023\u002Felongated-physiological-structure-segmentation-via-spatial-and-scale-uncertainty","Elongated Physiological Structure Segmentation via Spatial and Scale Uncertainty-Aware Network",[774,775,776,777,78,778,660],"Zhang, Yinglin","Xi, Ruiling","Fu, Huazhu","Towey, Dave","Higashita, Risa","https:\u002F\u002Fdoi.org\u002F10.1007\u002F978-3-031-43901-8_31","content:publications:2023:elongated-physiological-structure-segmentation-via-spatial-and-scale-uncertainty.md",{"_path":782,"title":783,"authors":784,"year":726,"doi":786,"venue":787,"_id":788},"\u002Fpublications\u002F2023\u002Fenhancing-container-port-traffic-simulation-by-data-driven-learning-based-method","Enhancing Container Port Traffic Simulation by Data-Driven Learning-Based Method with Sparse Data",[496,130,785,231,78],"Dong, Jing","https:\u002F\u002Fdoi.org\u002F10.2139\u002Fssrn.4581291","SSRN Electronic Journal","content:publications:2023:enhancing-container-port-traffic-simulation-by-data-driven-learning-based-method.md",{"_path":790,"title":791,"authors":792,"year":726,"doi":793,"venue":794,"_id":795},"\u002Fpublications\u002F2023\u002Fhierarchical-convit-with-attention-based-relational-reasoner-for-visual-analogic","Hierarchical ConViT with Attention-Based Relational Reasoner for Visual Analogical Reasoning",[614,658,512,78,683],"https:\u002F\u002Fdoi.org\u002F10.1609\u002Faaai.v37i1.25072","Proceedings of the AAAI Conference on Artificial Intelligence","content:publications:2023:hierarchical-convit-with-attention-based-relational-reasoner-for-visual-analogic.md",{"_path":797,"title":798,"authors":799,"year":726,"doi":800,"venue":801,"_id":802},"\u002Fpublications\u002F2023\u002Fmask-attack-detection-using-vascular-weighted-motion-robust-rppg-signals","Mask Attack Detection Using Vascular-Weighted Motion-Robust rPPG Signals",[657,512,78,659,660,683],"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ftifs.2023.3293949","IEEE Transactions on Information Forensics and Security","content:publications:2023:mask-attack-detection-using-vascular-weighted-motion-robust-rppg-signals.md",{"_path":804,"title":805,"authors":806,"year":726,"doi":809,"venue":390,"_id":810},"\u002Fpublications\u002F2023\u002Foptimal-low-rank-qr-decomposition-with-an-application-on-rp-tsod","Optimal Low-Rank QR Decomposition with an Application on RP-TSOD",[807,512,78,808],"Yu, Haiyan","Shen, Linlin","https:\u002F\u002Fdoi.org\u002F10.1007\u002F978-981-99-8181-6_35","content:publications:2023:optimal-low-rank-qr-decomposition-with-an-application-on-rp-tsod.md",{"_path":812,"title":813,"authors":814,"year":726,"doi":816,"venue":817,"_id":818},"\u002Fpublications\u002F2023\u002Fprediction-and-analysis-of-container-terminal-logistics-arrival-time-based-on-si","Prediction and Analysis of Container Terminal Logistics Arrival Time Based on Simulation Interactive Modeling: A Case Study of Ningbo Port",[815,103,78],"Wang, Ruoqi","https:\u002F\u002Fdoi.org\u002F10.3390\u002Fmath11153271","Mathematics","content:publications:2023:prediction-and-analysis-of-container-terminal-logistics-arrival-time-based-on-si.md",{"_path":820,"title":821,"authors":822,"year":726,"doi":823,"venue":91,"_id":824},"\u002Fpublications\u002F2023\u002Fsc-gan-structure-consistent-gan-for-modality-transfer-with-fft-and-multi-scale-p","SC-GAN: Structure Consistent GAN for Modality Transfer with FFT and Multi-Scale Perception",[775,774,78,778,660],"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fisbi53787.2023.10230436","content:publications:2023:sc-gan-structure-consistent-gan-for-modality-transfer-with-fft-and-multi-scale-p.md",{"_path":826,"title":827,"authors":828,"year":726,"doi":830,"venue":794,"_id":831},"\u002Fpublications\u002F2023\u002Fsiamese-discriminant-deep-reinforcement-learning-for-solving-jigsaw-puzzles-with","Siamese-Discriminant Deep Reinforcement Learning for Solving Jigsaw Puzzles with Large Eroded Gaps",[829,580,657,520,512,78],"Song, Xingke","https:\u002F\u002Fdoi.org\u002F10.1609\u002Faaai.v37i2.25325","content:publications:2023:siamese-discriminant-deep-reinforcement-learning-for-solving-jigsaw-puzzles-with.md",{"_path":833,"title":834,"authors":835,"year":726,"doi":837,"venue":838,"_id":839},"\u002Fpublications\u002F2023\u002Fstructural-priors-guided-network-for-the-corneal-endothelial-cell-segmentation","Structural Priors Guided Network for the Corneal Endothelial Cell Segmentation",[774,775,836,777,78,778,660],"Zeng, Lingxi","https:\u002F\u002Fdoi.org\u002F10.1109\u002Ftmi.2023.3300656","IEEE Transactions on Medical Imaging","content:publications:2023:structural-priors-guided-network-for-the-corneal-endothelial-cell-segmentation.md",{"_path":841,"title":842,"authors":843,"year":726,"doi":847,"venue":91,"_id":848},"\u002Fpublications\u002F2023\u002Fug-net-corneal-endothelial-cell-segmentation-based-on-uncertainty-estimation-and","UG-Net: Corneal Endothelial Cell Segmentation Based on Uncertainty Estimation and Soft Spatial Attention",[774,844,845,846,777,78,778,660],"Wang, Wei","Wang, Biao","Cai, Zichao","https:\u002F\u002Fdoi.org\u002F10.1109\u002Fisbi53787.2023.10230682","content:publications:2023:ug-net-corneal-endothelial-cell-segmentation-based-on-uncertainty-estimation-and.md",{"_path":850,"title":851,"authors":852,"year":853,"doi":854,"venue":151,"_id":855},"\u002Fpublications\u002F2024\u002Fa-cascaded-retrieval-while-reasoning-multi-document-comprehension-framework-with","A cascaded retrieval-while-reasoning multi-document comprehension framework with incremental attention for medical question answering",[533,512,78,705,479],2024,"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.eswa.2024.125701","content:publications:2024:a-cascaded-retrieval-while-reasoning-multi-document-comprehension-framework-with.md",{"_path":857,"title":858,"authors":859,"year":853,"doi":862,"venue":91,"_id":863},"\u002Fpublications\u002F2024\u002Fa-hierarchical-cooperative-genetic-programming-for-complex-piecewise-symbolic-re","A Hierarchical Cooperative Genetic Programming for Complex Piecewise Symbolic Regression",[496,860,78,130,861],"Yi, Wenjie","Jin, Yaochu","https:\u002F\u002Fdoi.org\u002F10.1109\u002Fcec60901.2024.10611754","content:publications:2024:a-hierarchical-cooperative-genetic-programming-for-complex-piecewise-symbolic-re.md",{"_path":865,"title":866,"authors":867,"year":853,"doi":869,"venue":151,"_id":870},"\u002Fpublications\u002F2024\u002Fa-pattern-based-algorithm-with-fuzzy-logic-bin-selector-for-online-bin-packing-p","A pattern-based algorithm with fuzzy logic bin selector for online bin packing problem",[712,103,203,615,78,130,868],"Garibaldi, Jonathan M.","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.eswa.2024.123515","content:publications:2024:a-pattern-based-algorithm-with-fuzzy-logic-bin-selector-for-online-bin-packing-p.md",{"_path":872,"title":873,"authors":874,"year":853,"doi":875,"venue":876,"_id":877},"\u002Fpublications\u002F2024\u002Fadvancing-container-port-traffic-simulation-a-data-driven-machine-learning-appro","Advancing container port traffic simulation: A data-driven machine learning approach in sparse data environments",[496,130,785,231,78],"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.asoc.2024.112190","Applied Soft Computing","content:publications:2024:advancing-container-port-traffic-simulation-a-data-driven-machine-learning-appro.md",{"_path":879,"title":880,"authors":881,"year":853,"doi":889,"venue":890,"_id":891},"\u002Fpublications\u002F2024\u002Fcausal-effects-of-adversarial-attacks-on-ai-models-in-6g-consumer-electronics","Causal Effects of Adversarial Attacks on AI Models in 6G Consumer Electronics",[882,883,884,885,886,78,887,888],"Guo, Da","Feng, Z.B.","Zhang, Zhen","Khan, Fazlullah","Chen, Chien‐Ming","Omar, Marwan","Kumari, Saru","https:\u002F\u002Fdoi.org\u002F10.1109\u002Ftce.2024.3443328","IEEE Transactions on Consumer Electronics","content:publications:2024:causal-effects-of-adversarial-attacks-on-ai-models-in-6g-consumer-electronics.md",{"_path":893,"title":894,"authors":895,"year":853,"doi":898,"venue":91,"_id":899},"\u002Fpublications\u002F2024\u002Fcharacterising-deep-learning-loss-landscapes-with-local-optima-networks","Characterising Deep Learning Loss Landscapes with Local Optima Networks",[896,897,78],"Zhou, Yuyang","Neri, Ferrante","https:\u002F\u002Fdoi.org\u002F10.1109\u002Fcec60901.2024.10611772","content:publications:2024:characterising-deep-learning-loss-landscapes-with-local-optima-networks.md",{"_path":901,"title":902,"authors":903,"year":853,"doi":904,"venue":118,"_id":905},"\u002Fpublications\u002F2024\u002Fdeep-reinforcement-learning-assisted-genetic-programming-ensemble-hyper-heuristi","Deep Reinforcement Learning Assisted Genetic Programming Ensemble Hyper-Heuristics for Dynamic Scheduling of Container Port Trucks",[496,78,130,785,861],"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ftevc.2024.3381042","content:publications:2024:deep-reinforcement-learning-assisted-genetic-programming-ensemble-hyper-heuristi.md",{"_path":907,"title":908,"authors":909,"year":853,"doi":912,"venue":913,"_id":914},"\u002Fpublications\u002F2024\u002Fdiscrete-time-survival-models-with-neural-networks-for-age-period-cohort-analysi","Discrete-Time Survival Models with Neural Networks for Age–Period–Cohort Analysis of Credit Risk",[910,911,130,78],"Wang, Hao","Bellotti, Anthony","https:\u002F\u002Fdoi.org\u002F10.3390\u002Frisks12020031","Risks","content:publications:2024:discrete-time-survival-models-with-neural-networks-for-age-period-cohort-analysi.md",{"_path":916,"title":917,"authors":918,"year":853,"doi":921,"venue":922,"_id":923},"\u002Fpublications\u002F2024\u002Fenhancing-online-yard-crane-scheduling-through-a-two-stage-rollout-memetic-genet","Enhancing online yard crane scheduling through a two-stage rollout memetic genetic programming",[919,78,896,496,920],"Jin, Chenwei","Tan, Leshan","https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs12293-024-00424-4","Memetic Computing","content:publications:2024:enhancing-online-yard-crane-scheduling-through-a-two-stage-rollout-memetic-genet.md",{"_path":925,"title":926,"authors":927,"year":853,"doi":935,"venue":91,"_id":936},"\u002Fpublications\u002F2024\u002Fevolution-assisted-deep-reinforcement-learning-for-fast-charging-station-coordin","Evolution-Assisted Deep Reinforcement Learning for Fast Charging Station Coordinated Operation",[928,929,930,931,932,933,203,934,78],"Yang, Xiaoying","Gu, Yujing","Jia, Fuhua","Li, Yiran","Wang, Hongru","Du, Nanjiang","Ye, Yujian","https:\u002F\u002Fdoi.org\u002F10.1109\u002Fcec60901.2024.10611768","content:publications:2024:evolution-assisted-deep-reinforcement-learning-for-fast-charging-station-coordin.md",{"_path":938,"title":939,"authors":940,"year":853,"doi":944,"venue":922,"_id":945},"\u002Fpublications\u002F2024\u002Fgase-graph-attention-sampling-with-edges-fusion-for-solving-vehicle-routing-prob","Gase: graph attention sampling with edges fusion for solving vehicle routing problems",[941,78,885,942,943],"Wang, Zhenwei","Özcan, Ender","Zhang, Tiehua","https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs12293-024-00428-0","content:publications:2024:gase-graph-attention-sampling-with-edges-fusion-for-solving-vehicle-routing-prob.md",{"_path":947,"title":948,"authors":949,"year":853,"doi":950,"venue":91,"_id":951},"\u002Fpublications\u002F2024\u002Fhierarchical-perceptual-and-predictive-analogy-inference-network-for-abstract-vi","Hierarchical Perceptual and Predictive Analogy-Inference Network for Abstract Visual Reasoning",[614,512,78,683],"https:\u002F\u002Fdoi.org\u002F10.1145\u002F3664647.3681246","content:publications:2024:hierarchical-perceptual-and-predictive-analogy-inference-network-for-abstract-vi.md",{"_path":953,"title":954,"authors":955,"year":853,"doi":959,"venue":960,"_id":961},"\u002Fpublications\u002F2024\u002Flow-contrast-medical-image-segmentation-via-transformer-and-boundary-perception","Low-Contrast Medical Image Segmentation via Transformer and Boundary Perception",[774,775,844,956,957,958,777,78,776,778,660],"Li, Heng","Hu, Lingxi","Lin, Huiyan","https:\u002F\u002Fdoi.org\u002F10.1109\u002Ftetci.2024.3353624","IEEE Transactions on Emerging Topics in Computational Intelligence","content:publications:2024:low-contrast-medical-image-segmentation-via-transformer-and-boundary-perception.md",{"_path":963,"title":964,"authors":965,"year":853,"doi":966,"venue":151,"_id":967},"\u002Fpublications\u002F2024\u002Fmedical-chief-complaint-classification-with-hierarchical-structure-of-label-desc","Medical chief complaint classification with hierarchical structure of label descriptions",[705,479,533,78],"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.eswa.2024.123938","content:publications:2024:medical-chief-complaint-classification-with-hierarchical-structure-of-label-desc.md",{"_path":969,"title":970,"authors":971,"year":853,"doi":973,"venue":151,"_id":974},"\u002Fpublications\u002F2024\u002Fmobile-robot-sequential-decision-making-using-a-deep-reinforcement-learning-hype","Mobile robot sequential decision making using a deep reinforcement learning hyper-heuristic approach",[203,928,930,972,934,78],"Jin, J.S.","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.eswa.2024.124959","content:publications:2024:mobile-robot-sequential-decision-making-using-a-deep-reinforcement-learning-hype.md",{"_path":976,"title":977,"authors":978,"year":853,"doi":980,"venue":91,"_id":981},"\u002Fpublications\u002F2024\u002Fmulti-view-spectrogram-transformer-for-respiratory-sound-classification","Multi-View Spectrogram Transformer for Respiratory Sound Classification",[614,979,512,78,683],"Yan, Yuchen","https:\u002F\u002Fdoi.org\u002F10.1109\u002Ficassp48485.2024.10445825","content:publications:2024:multi-view-spectrogram-transformer-for-respiratory-sound-classification.md",{"_path":983,"title":984,"authors":985,"year":853,"doi":987,"venue":787,"_id":988},"\u002Fpublications\u002F2024\u002Fpattern-based-learning-and-optimisation-through-pricing-for-bin-packing-problem","Pattern Based Learning and Optimisation Through Pricing for Bin Packing Problem",[618,78,986,103,712,512],"Liu, Tie‐Yan","https:\u002F\u002Fdoi.org\u002F10.2139\u002Fssrn.4822673","content:publications:2024:pattern-based-learning-and-optimisation-through-pricing-for-bin-packing-problem.md",{"_path":990,"title":991,"authors":992,"year":853,"doi":993,"venue":151,"_id":994},"\u002Fpublications\u002F2024\u002Fprogressively-orthogonally-mapped-efficientnet-for-action-recognition-on-time-ra","Progressively-orthogonally-mapped EfficientNet for action recognition on time-range-Doppler signature",[657,512,78,659,660,683],"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.eswa.2024.124824","content:publications:2024:progressively-orthogonally-mapped-efficientnet-for-action-recognition-on-time-ra.md",{"_path":996,"title":997,"authors":998,"year":853,"doi":999,"venue":735,"_id":1000},"\u002Fpublications\u002F2024\u002Fradar-gait-recognition-using-dual-branch-swin-transformer-with-asymmetric-attent","Radar gait recognition using Dual-branch Swin Transformer with Asymmetric Attention Fusion",[614,512,78,683],"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.patcog.2024.111101","content:publications:2024:radar-gait-recognition-using-dual-branch-swin-transformer-with-asymmetric-attent.md",{"_path":1002,"title":1003,"authors":1004,"year":853,"doi":1008,"venue":794,"_id":1009},"\u002Fpublications\u002F2024\u002Fscale-optimization-using-evolutionary-reinforcement-learning-for-object-detectio","Scale Optimization Using Evolutionary Reinforcement Learning for Object Detection on Drone Imagery",[658,928,614,512,1005,1006,78,1007,660],"Zhang, Qian","Zhao, Yitian","He, Xiangjian","https:\u002F\u002Fdoi.org\u002F10.1609\u002Faaai.v38i1.27795","content:publications:2024:scale-optimization-using-evolutionary-reinforcement-learning-for-object-detectio.md",{"_path":1011,"title":1012,"authors":1013,"year":853,"doi":1014,"venue":390,"_id":1015},"\u002Fpublications\u002F2024\u002Ftransformer-surrogate-genetic-programming-for-dynamic-container-port-truck-dispa","Transformer Surrogate Genetic Programming for Dynamic Container Port Truck Dispatching",[496,785,130,78],"https:\u002F\u002Fdoi.org\u002F10.1007\u002F978-981-97-2272-3_21","content:publications:2024:transformer-surrogate-genetic-programming-for-dynamic-container-port-truck-dispa.md",{"_path":1017,"title":1018,"authors":1019,"year":853,"doi":1020,"venue":735,"_id":1021},"\u002Fpublications\u002F2024\u002Ftwo-stage-rule-induction-visual-reasoning-on-rpms-with-an-application-to-video-p","Two-stage Rule-induction visual reasoning on RPMs with an application to video prediction",[614,512,78,683],"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.patcog.2024.111151","content:publications:2024:two-stage-rule-induction-visual-reasoning-on-rpms-with-an-application-to-video-p.md",{"_path":1023,"title":1024,"authors":1025,"year":1028,"doi":1029,"venue":876,"_id":1030},"\u002Fpublications\u002F2025\u002Fa-particle-swarm-optimization-based-ensemble-metaheuristic-for-long-term-transmi","A particle swarm optimization-based ensemble metaheuristic for long-term transmission network expansion planning",[1026,1027,78],"Hong, Libin","Wang, G. Gary",2025,"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.asoc.2025.113282","content:publications:2025:a-particle-swarm-optimization-based-ensemble-metaheuristic-for-long-term-transmi.md",{"_path":1032,"title":1033,"authors":1034,"year":1028,"doi":1040,"venue":1041,"_id":1042},"\u002Fpublications\u002F2025\u002Fa-review-of-medical-text-analysis-theory-and-practice","A review of medical text analysis: Theory and practice",[1035,1036,78,1037,1038,1039],"Chen, Yani","Zhang, Chunwu","Sun, Tengfang","Ding, Weiping","Wang, Ruili","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.inffus.2025.103024","Information Fusion","content:publications:2025:a-review-of-medical-text-analysis-theory-and-practice.md",{"_path":1044,"title":1045,"authors":1046,"year":1028,"doi":1048,"venue":1049,"_id":1050},"\u002Fpublications\u002F2025\u002Fan-effective-combination-of-mechanisms-for-particle-swarm-optimization-based-ens","An effective combination of mechanisms for particle swarm optimization-based ensemble strategy",[1026,1047,78,88,942],"Gu, Zhantao","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.swevo.2025.102154","Swarm and Evolutionary Computation","content:publications:2025:an-effective-combination-of-mechanisms-for-particle-swarm-optimization-based-ens.md",{"_path":1052,"title":1053,"authors":1054,"year":1028,"doi":1057,"venue":91,"_id":1058},"\u002Fpublications\u002F2025\u002Fceari-co-evolutionary-agents-for-reassembling-and-inpainting-puzzles-with-gaps-a","CEARI: Co-Evolutionary Agents for Reassembling and Inpainting Puzzles with Gaps and Missing Pieces",[829,1055,931,658,512,78,1056,683],"Shangguan, Jianxu","Chen, Xin","https:\u002F\u002Fdoi.org\u002F10.1145\u002F3746027.3754695","content:publications:2025:ceari-co-evolutionary-agents-for-reassembling-and-inpainting-puzzles-with-gaps-a.md",{"_path":1060,"title":1061,"authors":1062,"year":1028,"doi":1067,"venue":794,"_id":1068},"\u002Fpublications\u002F2025\u002Fdarr-a-dual-branch-arithmetic-regression-reasoning-framework-for-solving-machine","DARR: A Dual-Branch Arithmetic Regression Reasoning Framework for Solving Machine Number Reasoning",[1063,1064,1065,512,78,1006,1066,683],"Li, Chengtai","Tan, Yee Yang","He, Yuting","Yu, Heng","https:\u002F\u002Fdoi.org\u002F10.1609\u002Faaai.v39i2.32127","content:publications:2025:darr-a-dual-branch-arithmetic-regression-reasoning-framework-for-solving-machine.md",{"_path":1070,"title":1071,"authors":1072,"year":1028,"doi":1077,"venue":91,"_id":1078},"\u002Fpublications\u002F2025\u002Ffinemotion-a-dataset-and-benchmark-with-both-spatial-and-temporal-annotation-for","FineMotion: A Dataset and Benchmark with Both Spatial and Temporal Annotation for Fine-Grained Motion Generation and Editing",[1073,1074,1075,1076,512,78,130,808],"Wu, Bizhu","Xie, Jinheng","Ding, Meidan","Kong, Zhe","https:\u002F\u002Fdoi.org\u002F10.1109\u002Ficcv51701.2025.01284","content:publications:2025:finemotion-a-dataset-and-benchmark-with-both-spatial-and-temporal-annotation-for.md",{"_path":1080,"title":1081,"authors":1082,"year":1028,"doi":1087,"venue":1088,"_id":1089},"\u002Fpublications\u002F2025\u002Ffpga-routing-congestion-prediction-via-graph-learning-aided-conditional-gan","FPGA Routing Congestion Prediction via Graph Learning-Aided Conditional GAN",[1083,1084,1085,1065,1086,808,78,1066],"Yang, Qingyu","Li, Jingjin","Li, Rui","Ha, Yajun","https:\u002F\u002Fdoi.org\u002F10.1145\u002F3773770","ACM Transactions on Design Automation of Electronic Systems","content:publications:2025:fpga-routing-congestion-prediction-via-graph-learning-aided-conditional-gan.md",{"_path":1091,"title":1092,"authors":1093,"year":1028,"doi":1095,"venue":1096,"_id":1097},"\u002Fpublications\u002F2025\u002Fllm4netlist-llm-enabled-step-based-netlist-generation-from-natural-language-desc","LLM4Netlist: LLM-Enabled Step-Based Netlist Generation From Natural Language Description",[1094,1083,479,1066,203,78,808],"Ye, Kailiang","https:\u002F\u002Fdoi.org\u002F10.1109\u002Fjetcas.2025.3568548","IEEE Journal on Emerging and Selected Topics in Circuits and Systems","content:publications:2025:llm4netlist-llm-enabled-step-based-netlist-generation-from-natural-language-desc.md",{"_path":1099,"title":1100,"authors":1101,"year":1028,"doi":1104,"venue":1105,"_id":1106},"\u002Fpublications\u002F2025\u002Fonline-bayesian-approximation-based-uncertainty-aware-model-for-ophthalmic-image","Online Bayesian Approximation Based Uncertainty Aware Model for Ophthalmic Image Segmentation",[774,778,836,1102,775,1103,776,777,78,660],"Li, Jialin","Liu, Tianhang","https:\u002F\u002Fdoi.org\u002F10.1109\u002Fjbhi.2025.3593983","IEEE Journal of Biomedical and Health Informatics","content:publications:2025:online-bayesian-approximation-based-uncertainty-aware-model-for-ophthalmic-image.md",{"_path":1108,"title":1109,"authors":1110,"year":1028,"doi":1111,"venue":1112,"_id":1113},"\u002Fpublications\u002F2025\u002Fpgu-sgp-a-pheno-geno-unified-surrogate-genetic-programming-for-real-life-contain","PGU-SGP: A Pheno-Geno Unified Surrogate Genetic Programming For Real-life Container Terminal Truck Scheduling",[920,919,496,130,78],"https:\u002F\u002Fdoi.org\u002F10.1145\u002F3712256.3726326","Proceedings of the Genetic and Evolutionary Computation Conference","content:publications:2025:pgu-sgp-a-pheno-geno-unified-surrogate-genetic-programming-for-real-life-contain.md",{"_path":1115,"title":1116,"authors":1117,"year":1028,"doi":1119,"venue":1112,"_id":1120},"\u002Fpublications\u002F2025\u002Fsiamnas-siamese-surrogate-model-for-dominance-relation-prediction-in-multi-objec","SiamNAS: Siamese Surrogate Model for Dominance Relation Prediction in Multi-objective Neural Architecture Search",[896,897,1118,78],"Ong, Yew-Soon","https:\u002F\u002Fdoi.org\u002F10.1145\u002F3712256.3726359","content:publications:2025:siamnas-siamese-surrogate-model-for-dominance-relation-prediction-in-multi-objec.md",{"_path":1122,"title":1123,"authors":1124,"year":1028,"doi":1127,"venue":787,"_id":1128},"\u002Fpublications\u002F2025\u002Ftdcgait-a-temporal-doppler-concept-tri-branch-framework-for-radar-gait-recogniti","TDCGait: A Temporal-Doppler-Concept Tri-branch Framework for Radar Gait Recognition",[1125,614,512,78,1126,683],"He, Zhongkun","Guo, Lijun","https:\u002F\u002Fdoi.org\u002F10.2139\u002Fssrn.5436568","content:publications:2025:tdcgait-a-temporal-doppler-concept-tri-branch-framework-for-radar-gait-recogniti.md",{"_path":1130,"title":1131,"authors":1132,"year":1028,"doi":1137,"venue":197,"_id":1138},"\u002Fpublications\u002F2025\u002Ftscf-net-a-temporal-spectral-cross-fusion-network-for-low-channel-eeg-motor-imag","TSCF-Net: A Temporal-Spectral Cross-Fusion Network for Low-Channel EEG Motor Imagery Classification",[1133,1134,1135,78,1136],"Jiao, Yang","Cui, Mingzhe","Chen, Tao","Pan, Yi","https:\u002F\u002Fdoi.org\u002F10.1007\u002F978-981-95-0695-8_3","content:publications:2025:tscf-net-a-temporal-spectral-cross-fusion-network-for-low-channel-eeg-motor-imag.md",{"_path":1140,"title":1141,"authors":1142,"year":1145,"doi":1146,"venue":151,"_id":1147},"\u002Fpublications\u002F2026\u002Fmela-a-metacognitive-llm-driven-architecture-for-automatic-heuristic-design","MeLA: A metacognitive LLM-driven architecture for automatic heuristic design",[1143,496,1144,78],"Qiu, Zishang","Chen, Long",2026,"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.eswa.2026.133022","content:publications:2026:mela-a-metacognitive-llm-driven-architecture-for-automatic-heuristic-design.md",{"_path":1149,"title":1150,"authors":1151,"year":1145,"doi":1153,"venue":151,"_id":1154},"\u002Fpublications\u002F2026\u002Fonline-risk-aware-pattern-adjustment-for-bin-packing-problem","Online risk-aware pattern adjustment for bin packing problem",[618,1152,78],"Liu, Tie-Yan","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.eswa.2025.131074","content:publications:2026:online-risk-aware-pattern-adjustment-for-bin-packing-problem.md",{"_path":1156,"title":1157,"authors":1158,"year":1145,"doi":1159,"venue":1160,"_id":1161},"\u002Fpublications\u002F2026\u002Fpredictive-reasoning-with-augmented-anomaly-contrastive-learning-for-composition","Predictive Reasoning with Augmented Anomaly Contrastive Learning for Compositional Visual Relations",[1063,1065,512,78,1006,1066,683],"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ftmm.2026.3668614","IEEE Transactions on Multimedia","content:publications:2026:predictive-reasoning-with-augmented-anomaly-contrastive-learning-for-composition.md",{"_path":1163,"title":1164,"authors":1165,"year":1145,"doi":1169,"venue":265,"_id":1170},"\u002Fpublications\u002F2026\u002Fpreference-agile-multi-objective-optimization-for-real-time-vehicle-dispatching","Preference-agile multi-objective optimization for real-time vehicle dispatching",[580,1166,130,512,1167,1168,78],"Zhao, Wenhao","Chen, Xin’an","Zhang, Qingfu","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.ejor.2026.04.017","content:publications:2026:preference-agile-multi-objective-optimization-for-real-time-vehicle-dispatching.md",{"_path":1172,"title":1173,"authors":1174,"year":1145,"doi":1177,"venue":1160,"_id":1178},"\u002Fpublications\u002F2026\u002Franking-based-self-supervised-representation-learning-for-skeleton-based-action","Ranking-Based Self-Supervised Representation Learning for Skeleton-Based Action Recognition",[1073,1175,1074,1176,512,78,130,808],"Chen, Junliang","Li, Qiufu","https:\u002F\u002Fdoi.org\u002F10.1109\u002Ftmm.2026.3654466","content:publications:2026:ranking-based-self-supervised-representation-learning-for-skeleton-based-action.md",{"_path":1180,"title":1181,"authors":1182,"year":1145,"doi":1184,"venue":1185,"_id":1186},"\u002Fpublications\u002F2026\u002Fs-sup3-sup-dl-sample-aggregated-structured-supervised-dictionary-learning","S \u003Csup>3\u003C\u002Fsup> DL: Sample-Aggregated Structured Supervised Dictionary Learning",[807,1183,512,808,1056,78],"Peng, Yucheng","https:\u002F\u002Fdoi.org\u002F10.1109\u002Flsp.2026.3704064","IEEE Signal Processing Letters","content:publications:2026:s-sup3-sup-dl-sample-aggregated-structured-supervised-dictionary-learning.md",{"_path":1188,"title":1189,"authors":1190,"year":1145,"doi":1195,"venue":197,"_id":1196},"\u002Fpublications\u002F2026\u002Fscheduling-heuristic-learning-via-genetic-programming-for-dynamic-flexible-job-s","Scheduling Heuristic Learning via Genetic Programming for Dynamic Flexible Job Shop Scheduling with Heterogeneous Batch Arrivals",[1191,1192,1193,1194,78],"Zhu, Luyao","Zhang, Fangfang","Mei, Yi","Zhang, Mengjie","https:\u002F\u002Fdoi.org\u002F10.1007\u002F978-981-95-7081-2_49","content:publications:2026:scheduling-heuristic-learning-via-genetic-programming-for-dynamic-flexible-job-s.md",1782639406362]