[{"data":1,"prerenderedAt":1002},["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,[74,81,91,97,109,119,124,134,141,147,155,160,164,171,178,188,194,200,206,217,224,229,237,245,253,259,264,278,285,290,298,304,312,318,329,335,342,347,355,361,367,373,378,384,395,402,408,414,420,426,432,441,447,452,458,466,472,477,483,492,499,504,509,515,521,527,533,549,555,561,566,572,577,582,588,596,605,611,616,622,628,634,640,645,650,656,661,668,673,679,685,695,703,711,716,721,733,738,744,749,754,760,774,782,787,793,799,804,809,814,826,831,836,843,851,856,861,866,871,876,882,894,900,905,910,915,928,934,940,946,951,956,961,970,977,983,992,997],{"_path":75,"title":76,"year":77,"doi":78,"venue":79,"_id":80},"\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",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":82,"title":83,"authors":84,"year":87,"doi":88,"venue":89,"_id":90},"\u002Fpublications\u002F2009\u002Fcanonical-representation-genetic-programming","Canonical representation genetic programming",[85,86],"Woodward, John R.","Bai, Ruibin",2009,"https:\u002F\u002Fdoi.org\u002F10.1145\u002F1543834.1543914",null,"content:publications:2009:canonical-representation-genetic-programming.md",{"_path":92,"title":93,"authors":94,"year":87,"doi":95,"venue":89,"_id":96},"\u002Fpublications\u002F2009\u002Fwhy-evolution-is-not-a-good-paradigm-for-program-induction","Why evolution is not a good paradigm for program induction",[85,86],"https:\u002F\u002Fdoi.org\u002F10.1145\u002F1543834.1543915","content:publications:2009:why-evolution-is-not-a-good-paradigm-for-program-induction.md",{"_path":98,"title":99,"authors":100,"year":106,"doi":107,"venue":89,"_id":108},"\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",[101,102,103,104,105,86],"Li, Jiawei","Kendall, Graham","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":110,"title":111,"authors":112,"year":106,"doi":116,"venue":117,"_id":118},"\u002Fpublications\u002F2010\u002Fa-hybrid-evolutionary-approach-to-the-nurse-rostering-problem","A Hybrid Evolutionary Approach to the Nurse Rostering Problem",[86,113,102,114,115],"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":120,"title":121,"year":106,"doi":122,"venue":89,"_id":123},"\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","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":125,"title":126,"authors":127,"year":130,"doi":131,"venue":132,"_id":133},"\u002Fpublications\u002F2011\u002Ftabu-assisted-guided-local-search-approaches-for-freight-service-network-design","Tabu assisted guided local search approaches for freight service network design",[86,102,128,129],"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":135,"title":136,"year":137,"doi":138,"venue":139,"_id":140},"\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",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":142,"title":143,"year":137,"doi":144,"venue":145,"_id":146},"\u002Fpublications\u002F2012\u002Fevidence-and-belief-in-regulatory-decisions-incorporating-expected-utility-into","Evidence and belief in regulatory decisions – Incorporating expected utility","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":148,"title":149,"authors":150,"year":151,"doi":152,"venue":153,"_id":154},"\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",[86,101,129,102],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":156,"title":157,"year":151,"doi":158,"venue":153,"_id":159},"\u002Fpublications\u002F2013\u002Fa-path-oriented-encoding-evolutionary-algorithm-for-network-coding-resource-mini","A path-oriented encoding evolutionary algorithm for network coding resource","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":161,"title":162,"year":151,"doi":89,"venue":89,"_id":163},"\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","content:publications:2013:a-study-of-node-based-large-neighbourhood-approaches-for-the-logistics-service-n.md",{"_path":165,"title":166,"authors":167,"year":151,"doi":169,"venue":89,"_id":170},"\u002Fpublications\u002F2013\u002Fa-task-based-approach-for-a-real-world-commodity-routing-problem","A task based approach for a real-world commodity routing problem",[168,86,128,102],"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":172,"title":173,"authors":174,"year":151,"doi":176,"venue":145,"_id":177},"\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",[175,86],"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":179,"title":180,"authors":181,"year":151,"doi":185,"venue":186,"_id":187},"\u002Fpublications\u002F2013\u002Fswarm-intelligence-in-big-data-analytics","Swarm Intelligence in Big Data Analytics",[182,183,184,86],"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":189,"title":190,"year":191,"doi":192,"venue":89,"_id":193},"\u002Fpublications\u002F2014\u002Fa-combinatorial-algorithm-for-the-cardinality-constrained-portfolio-optimization","A combinatorial algorithm for the cardinality constrained portfolio optimization",2014,"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fcec.2014.6900357","content:publications:2014:a-combinatorial-algorithm-for-the-cardinality-constrained-portfolio-optimization.md",{"_path":195,"title":196,"year":191,"doi":197,"venue":198,"_id":199},"\u002Fpublications\u002F2014\u002Fa-strategic-approach-to-improve-sustainability-in-transportation-service-procure","A strategic approach to improve sustainability in transportation service","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":201,"title":202,"year":191,"doi":203,"venue":204,"_id":205},"\u002Fpublications\u002F2014\u002Fhybridising-heuristics-within-an-estimation-distribution-algorithm-for-examinati","Hybridising heuristics within an estimation distribution algorithm for","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":207,"title":208,"authors":209,"year":191,"doi":214,"venue":215,"_id":216},"\u002Fpublications\u002F2014\u002Flife-cycle-resource-consumption-of-automotive-power-seats","Life cycle resource consumption of automotive power seats",[210,211,212,213,86],"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":218,"title":219,"authors":220,"year":191,"doi":222,"venue":89,"_id":223},"\u002Fpublications\u002F2014\u002Fmaintaining-population-diversity-in-brain-storm-optimization-algorithm","Maintaining population diversity in brain storm optimization algorithm",[182,183,184,221,86],"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":225,"title":226,"year":191,"doi":227,"venue":89,"_id":228},"\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","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":230,"title":231,"authors":232,"year":191,"doi":234,"venue":235,"_id":236},"\u002Fpublications\u002F2014\u002Fpopulation-diversity-maintenance-in-brain-storm-optimization-algorithm","Population Diversity Maintenance In Brain Storm Optimization Algorithm",[182,183,184,233,86],"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":238,"title":239,"authors":240,"year":191,"doi":242,"venue":243,"_id":244},"\u002Fpublications\u002F2014\u002Fsearch-with-evolutionary-ruin-and-stochastic-rebuild-a-theoretic-framework-and-a","Search with evolutionary ruin and stochastic rebuild: A theoretic framework an",[114,86,241,128],"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":246,"title":247,"authors":248,"year":191,"doi":250,"venue":251,"_id":252},"\u002Fpublications\u002F2014\u002Fstochastic-service-network-design-with-rerouting","Stochastic service network design with rerouting",[86,249,114,175],"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":254,"title":255,"year":256,"doi":257,"venue":89,"_id":258},"\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",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":260,"title":261,"year":256,"doi":262,"venue":251,"_id":263},"\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","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":265,"title":266,"authors":267,"year":256,"doi":276,"venue":153,"_id":277},"\u002Fpublications\u002F2015\u002Fgood-laboratory-practice-for-optimization-research","Good Laboratory Practice for optimization research",[102,86,268,269,270,271,101,115,272,128,273,274,275],"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":279,"title":280,"authors":281,"year":282,"doi":283,"venue":89,"_id":284},"\u002Fpublications\u002F2016\u002Fa-dynamic-truck-dispatching-problem-in-marine-container-terminal","A dynamic truck dispatching problem in marine container terminal",[168,86,213,128,102],2016,"https:\u002F\u002Fdoi.org\u002F10.1109\u002Fssci.2016.7850081","content:publications:2016:a-dynamic-truck-dispatching-problem-in-marine-container-terminal.md",{"_path":286,"title":287,"year":282,"doi":288,"venue":89,"_id":289},"\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","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":291,"title":292,"authors":293,"year":282,"doi":295,"venue":296,"_id":297},"\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",[294,86,129,102],"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":299,"title":300,"year":282,"doi":301,"venue":302,"_id":303},"\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","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":305,"title":306,"authors":307,"year":282,"doi":310,"venue":89,"_id":311},"\u002Fpublications\u002F2016\u002Fa-variable-neighbourhood-search-algorithm-with-compound-neighbourhoods-for-vrptw","A Variable Neighbourhood Search Algorithm with Compound Neighbourhoods for VRPTW",[308,128,86,309],"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":313,"title":314,"year":282,"doi":315,"venue":316,"_id":317},"\u002Fpublications\u002F2016\u002Fcold-chain-configuration-design-location-allocation-decision-making-using-coordi","Cold chain configuration design: location-allocation decision-making usin","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":319,"title":320,"authors":321,"year":282,"doi":89,"venue":327,"_id":328},"\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",[322,323,324,325,86,326],"Chaudhuri, Atanu","Dukovska‐Popovska, Iskra","Chan, Hing Kai","Subramanian, Nachiappan","Pawar, Kulwant S.","VBN Forskningsportal (Aalborg Universitet)","content:publications:2016:development-of-a-framework-for-big-data-analytics-in-cold-chain-logistics.md",{"_path":330,"title":331,"year":282,"doi":332,"venue":333,"_id":334},"\u002Fpublications\u002F2016\u002Fenvironmental-and-financial-performance-of-mechanical-recycling-of-carbon-fibre","Environmental and financial performance of mechanical recycling of carbon fibre","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":336,"title":337,"authors":338,"year":282,"doi":340,"venue":89,"_id":341},"\u002Fpublications\u002F2016\u002Ffreight-vehicle-travel-time-prediction-using-gradient-boosting-regression-tree","Freight Vehicle Travel Time Prediction Using Gradient Boosting Regression Tree",[339,86],"Li, Xia","https:\u002F\u002Fdoi.org\u002F10.1109\u002Ficmla.2016.0182","content:publications:2016:freight-vehicle-travel-time-prediction-using-gradient-boosting-regression-tree.md",{"_path":343,"title":344,"year":282,"doi":345,"venue":186,"_id":346},"\u002Fpublications\u002F2016\u002Ffreight-vehicle-travel-time-prediction-using-sparse-gaussian-processes-regressio","Freight Vehicle Travel Time Prediction Using Sparse Gaussian Processes","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":348,"title":349,"authors":350,"year":351,"doi":352,"venue":353,"_id":354},"\u002Fpublications\u002F2017\u002Fan-investigation-on-compound-neighborhoods-for-vrptw","An Investigation on Compound Neighborhoods for VRPTW",[308,128,86,309],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":356,"title":357,"year":351,"doi":358,"venue":359,"_id":360},"\u002Fpublications\u002F2017\u002Fcycle-slip-detection-for-triple-frequency-gps-observations-under-ionospheric-sci","Cycle-slip Detection for Triple-frequency GPS Observations Under Ionospheric","https:\u002F\u002Fdoi.org\u002F10.33012\u002F2017.15326","Proceedings of the Satellite Division's International Technical Meeting","content:publications:2017:cycle-slip-detection-for-triple-frequency-gps-observations-under-ionospheric-sci.md",{"_path":362,"title":363,"year":351,"doi":364,"venue":365,"_id":366},"\u002Fpublications\u002F2017\u002Foptimisation-of-transportation-service-network-using-k-node-large-neighbourhood","Optimisation of transportation service network using κ -node large neighbourhood","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":368,"title":369,"year":370,"doi":371,"venue":204,"_id":372},"\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",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":374,"title":375,"year":370,"doi":376,"venue":89,"_id":377},"\u002Fpublications\u002F2018\u002Fautomated-prediction-of-shopping-behaviours-using-taxi-trajectory-data-and-socia","Automated prediction of shopping behaviours using taxi trajectory data and","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":379,"title":380,"year":370,"doi":381,"venue":382,"_id":383},"\u002Fpublications\u002F2018\u002Fdecision-making-in-cold-chain-logistics-using-data-analytics-a-literature-review","Decision-making in cold chain logistics using data analytics: a literatur","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":385,"title":386,"authors":387,"year":370,"doi":393,"venue":89,"_id":394},"\u002Fpublications\u002F2018\u002Fspatio-temporal-prediction-of-shopping-behaviours-using-taxi-trajectory-data","Spatio-temporal prediction of shopping behaviours using taxi trajectory data",[388,389,86,390,391,392],"Cartlidge, John","Gong, Shuhui","Yue, Yang","Li, Qingquan","Qiu, Guoping","https:\u002F\u002Fdoi.org\u002F10.1109\u002Ficbda.2018.8367660","content:publications:2018:spatio-temporal-prediction-of-shopping-behaviours-using-taxi-trajectory-data.md",{"_path":396,"title":397,"year":398,"doi":399,"venue":400,"_id":401},"\u002Fpublications\u002F2019\u002Fa-hybrid-combinatorial-approach-to-a-two-stage-stochastic-portfolio-optimization","A hybrid combinatorial approach to a two-stage stochastic portfolio optimization",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":403,"title":404,"year":398,"doi":405,"venue":406,"_id":407},"\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","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":409,"title":410,"year":398,"doi":411,"venue":412,"_id":413},"\u002Fpublications\u002F2019\u002Fa-variable-neighborhood-search-algorithm-with-reinforcement-learning-for-a-real","A variable neighborhood search algorithm with reinforcement learning for a","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":415,"title":416,"authors":417,"year":398,"doi":418,"venue":89,"_id":419},"\u002Fpublications\u002F2019\u002Factivity-modelling-using-journey-pairing-of-taxi-trajectory-data","Activity Modelling Using Journey Pairing of Taxi Trajectory Data",[389,388,86,390,391,392],"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ficbda.2019.8712832","content:publications:2019:activity-modelling-using-journey-pairing-of-taxi-trajectory-data.md",{"_path":421,"title":422,"year":398,"doi":423,"venue":424,"_id":425},"\u002Fpublications\u002F2019\u002Fextracting-activity-patterns-from-taxi-trajectory-data-a-two-layer-framework-usi","Extracting activity patterns from taxi trajectory data: a two-layer framewor","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":427,"title":428,"year":398,"doi":429,"venue":430,"_id":431},"\u002Fpublications\u002F2019\u002Fregular-expression-based-medical-text-classification-using-constructive-heuristi","Regular Expression Based Medical Text Classification Using Constructive","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":433,"title":434,"authors":435,"year":398,"doi":438,"venue":439,"_id":440},"\u002Fpublications\u002F2019\u002Ftravel-time-prediction-in-transport-and-logistics","Travel time prediction in transport and logistics",[339,86,436,437],"Siebers, Peer‐Olaf","Wagner, Christian","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":442,"title":443,"year":444,"doi":445,"venue":89,"_id":446},"\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",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":448,"title":449,"year":444,"doi":450,"venue":243,"_id":451},"\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","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":453,"title":454,"year":444,"doi":455,"venue":456,"_id":457},"\u002Fpublications\u002F2020\u002Fa-multiobjective-single-bus-corridor-scheduling-using-machine-learning-based-pre","A multiobjective single bus corridor scheduling using machine learning-based","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":459,"title":460,"authors":461,"year":444,"doi":464,"venue":430,"_id":465},"\u002Fpublications\u002F2020\u002Fa-regularized-attribute-weighting-framework-for-naive-bayes","A Regularized Attribute Weighting Framework for Naive Bayes",[462,463,86],"Wang, Shihe","Ren, Jianfeng","https:\u002F\u002Fdoi.org\u002F10.1109\u002Faccess.2020.3044946","content:publications:2020:a-regularized-attribute-weighting-framework-for-naive-bayes.md",{"_path":467,"title":468,"authors":469,"year":444,"doi":470,"venue":89,"_id":471},"\u002Fpublications\u002F2020\u002Fdata-driven-agent-based-model-of-intra-urban-activities","Data-Driven Agent-Based Model of Intra-Urban Activities",[389,388,86,390,391,392],"https:\u002F\u002Fdoi.org\u002F10.1109\u002Ficbda49040.2020.9101327","content:publications:2020:data-driven-agent-based-model-of-intra-urban-activities.md",{"_path":473,"title":474,"year":444,"doi":475,"venue":89,"_id":476},"\u002Fpublications\u002F2020\u002Fdata-driven-regular-expressions-evolution-for-medical-text-classification-using","Data-Driven Regular Expressions Evolution for Medical Text Classification Using","https:\u002F\u002Fdoi.org\u002F10.1109\u002Fcec48606.2020.9185500","content:publications:2020:data-driven-regular-expressions-evolution-for-medical-text-classification-using.md",{"_path":478,"title":479,"year":444,"doi":480,"venue":481,"_id":482},"\u002Fpublications\u002F2020\u002Fforecasting-stock-market-return-with-nonlinearity-a-genetic-programming-approach","Forecasting stock market return with nonlinearity: a genetic programmin","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":484,"title":485,"authors":486,"year":444,"doi":489,"venue":490,"_id":491},"\u002Fpublications\u002F2020\u002Ffuzzy-c-means-based-scenario-bundling-for-stochastic-service-network-design","Fuzzy C-means-based scenario bundling for stochastic service network design",[294,86,487,488],"Landa-Silva, Dario","Aickelin, Uwe","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":493,"title":494,"authors":495,"year":444,"doi":496,"venue":497,"_id":498},"\u002Fpublications\u002F2020\u002Fgeographical-and-temporal-huff-model-calibration-using-taxi-trajectory-data","Geographical and temporal huff model calibration using taxi trajectory data",[389,388,86,390,391,392],"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":500,"title":501,"year":444,"doi":502,"venue":490,"_id":503},"\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","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":505,"title":506,"year":444,"doi":507,"venue":365,"_id":508},"\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","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":510,"title":511,"year":512,"doi":513,"venue":243,"_id":514},"\u002Fpublications\u002F2021\u002Fa-deep-reinforcement-learning-based-hyper-heuristic-for-combinatorial-optimisati","A deep reinforcement learning based hyper-heuristic for combinatorial",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":516,"title":517,"year":512,"doi":518,"venue":519,"_id":520},"\u002Fpublications\u002F2021\u002Fa-fuzzy-based-heuristic-algorithm-for-online-outbound-container-stacking-problem","A Fuzzy-based Heuristic Algorithm for Online Outbound Container Stacking Problem","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":522,"title":523,"year":512,"doi":524,"venue":525,"_id":526},"\u002Fpublications\u002F2021\u002Fa-genetic-optimization-resampling-based-particle-filtering-algorithm-for-indoor","A Genetic Optimization Resampling Based Particle Filtering Algorithm for Indoor","https:\u002F\u002Fdoi.org\u002F10.3390\u002Frs13010132","Remote Sensing","content:publications:2021:a-genetic-optimization-resampling-based-particle-filtering-algorithm-for-indoor.md",{"_path":528,"title":529,"year":512,"doi":530,"venue":531,"_id":532},"\u002Fpublications\u002F2021\u002Fa-hybrid-medical-text-classification-framework-integrating-attentive-rule-constr","A hybrid medical text classification framework: Integrating attentive rul","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":534,"title":535,"authors":536,"year":512,"doi":547,"venue":456,"_id":548},"\u002Fpublications\u002F2021\u002Fanalytics-and-machine-learning-in-vehicle-routing-research","Analytics and machine learning in vehicle routing research",[86,537,538,539,389,540,294,541,542,102,101,543,463,544,545,546],"Chen, Xinan","Chen, Zhi‐Long","Cui, Tianxiang","He, Wentao","Jin, Huan","Jin, Jiahuan","Lu, Zheng Feng","Weng, Paul","Xue, Ning","Zhang, Huayan","https:\u002F\u002Fdoi.org\u002F10.1080\u002F00207543.2021.2013566","content:publications:2021:analytics-and-machine-learning-in-vehicle-routing-research.md",{"_path":550,"title":551,"year":512,"doi":552,"venue":553,"_id":554},"\u002Fpublications\u002F2021\u002Fcollective-strategies-with-a-master-slave-mechanism-dominate-in-spatial-iterated","Collective Strategies With a Master-Slave Mechanism Dominate in Spatial-Iterated","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":556,"title":557,"authors":558,"year":512,"doi":559,"venue":490,"_id":560},"\u002Fpublications\u002F2021\u002Fdata-augmentation-by-morphological-mixup-for-solving-raven-s-progressive-matrice","Data augmentation by morphological mixup for solving Raven's Progressive Matrices",[540,463,86],"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":562,"title":563,"year":512,"doi":564,"venue":89,"_id":565},"\u002Fpublications\u002F2021\u002Fevolutionary-inspired-strategy-for-particle-distribution-optimization-in-auxilia","Evolutionary-Inspired Strategy for Particle Distribution Optimization in","https:\u002F\u002Fdoi.org\u002F10.1109\u002Fipin51156.2021.9662586","content:publications:2021:evolutionary-inspired-strategy-for-particle-distribution-optimization-in-auxilia.md",{"_path":567,"title":568,"year":512,"doi":569,"venue":570,"_id":571},"\u002Fpublications\u002F2021\u002Fnovel-prior-position-determination-approaches-in-particle-filter-for-ultra-wideb","Novel prior position determination approaches in particle filter for ultra","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":573,"title":574,"authors":575,"year":512,"doi":89,"venue":490,"_id":576},"\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",[540,463,86],"content:publications:2021:one-shot-visual-reasoning-on-rpms-with-an-application-to-video-frame-prediction.md",{"_path":578,"title":579,"year":512,"doi":580,"venue":89,"_id":581},"\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","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":583,"title":584,"year":585,"doi":586,"venue":570,"_id":587},"\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",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":589,"title":590,"authors":591,"year":585,"doi":593,"venue":594,"_id":595},"\u002Fpublications\u002F2022\u002Fan-improved-ant-colony-approach-for-the-competitive-traveling-salesmen-problem","An Improved Ant Colony Approach for the Competitive Traveling Salesmen Problem",[592,86,539,128,101],"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":597,"title":598,"authors":599,"year":585,"doi":602,"venue":603,"_id":604},"\u002Fpublications\u002F2022\u002Fboosting-the-discriminant-power-of-naive-bayes","Boosting the Discriminant Power of Naive Bayes",[462,463,600,86,601],"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":606,"title":607,"year":585,"doi":608,"venue":609,"_id":610},"\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","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":612,"title":613,"year":585,"doi":614,"venue":117,"_id":615},"\u002Fpublications\u002F2022\u002Fcooperative-double-layer-genetic-programming-hyper-heuristic-for-online-containe","Cooperative Double-Layer Genetic Programming Hyper-Heuristic for Online","https:\u002F\u002Fdoi.org\u002F10.1109\u002Ftevc.2022.3209985","content:publications:2022:cooperative-double-layer-genetic-programming-hyper-heuristic-for-online-containe.md",{"_path":617,"title":618,"year":585,"doi":619,"venue":620,"_id":621},"\u002Fpublications\u002F2022\u002Fidentify-patterns-in-online-bin-packing-problem-an-adaptive-pattern-based-algori","Identify Patterns in Online Bin Packing Problem: An Adaptive Pattern-Base","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":623,"title":624,"authors":625,"year":585,"doi":626,"venue":243,"_id":627},"\u002Fpublications\u002F2022\u002Flagrange-dual-bound-computation-for-stochastic-service-network-design","Lagrange dual bound computation for stochastic service network design",[294,86,463,101,102],"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":629,"title":630,"year":631,"doi":632,"venue":145,"_id":633},"\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",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":635,"title":636,"year":631,"doi":637,"venue":638,"_id":639},"\u002Fpublications\u002F2023\u002Fa-max-relevance-min-divergence-criterion-for-data-discretization-with-applicatio","A Max-Relevance-Min-Divergence criterion for data discretization with","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":641,"title":642,"year":631,"doi":643,"venue":145,"_id":644},"\u002Fpublications\u002F2023\u002Fa-semi-supervised-adaptive-discriminative-discretization-method-improving-discri","A semi-supervised adaptive discriminative discretization method improving","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.eswa.2023.120094","content:publications:2023:a-semi-supervised-adaptive-discriminative-discretization-method-improving-discri.md",{"_path":646,"title":647,"year":631,"doi":648,"venue":89,"_id":649},"\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","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":651,"title":652,"authors":653,"year":631,"doi":654,"venue":456,"_id":655},"\u002Fpublications\u002F2023\u002Fanalytics-and-machine-learning-in-scheduling-and-routing-research","Analytics and machine learning in scheduling and routing research",[86,538,102],"https:\u002F\u002Fdoi.org\u002F10.1080\u002F00207543.2022.2131930","content:publications:2023:analytics-and-machine-learning-in-scheduling-and-routing-research.md",{"_path":657,"title":658,"year":631,"doi":659,"venue":243,"_id":660},"\u002Fpublications\u002F2023\u002Fcontainer-port-truck-dispatching-optimization-using-real2sim-based-deep-reinforc","Container port truck dispatching optimization using Real2Sim based deep","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":662,"title":663,"authors":664,"year":631,"doi":665,"venue":666,"_id":667},"\u002Fpublications\u002F2023\u002Fdata-augmentation-by-morphological-mixup-for-solving-raven-s-progressive-matrice","Data augmentation by morphological mixup for solving Raven’s progressive matrices",[540,463,86],"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":669,"title":670,"year":631,"doi":671,"venue":186,"_id":672},"\u002Fpublications\u002F2023\u002Felongated-physiological-structure-segmentation-via-spatial-and-scale-uncertainty","Elongated Physiological Structure Segmentation via Spatial and Scale","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":674,"title":675,"year":631,"doi":676,"venue":677,"_id":678},"\u002Fpublications\u002F2023\u002Fenhancing-container-port-traffic-simulation-by-data-driven-learning-based-method","Enhancing Container Port Traffic Simulation by Data-Driven Learning-Based Method","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":680,"title":681,"year":631,"doi":682,"venue":683,"_id":684},"\u002Fpublications\u002F2023\u002Fhierarchical-convit-with-attention-based-relational-reasoner-for-visual-analogic","Hierarchical ConViT with Attention-Based Relational Reasoner for Visual","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":686,"title":687,"authors":688,"year":631,"doi":692,"venue":693,"_id":694},"\u002Fpublications\u002F2023\u002Fmask-attack-detection-using-vascular-weighted-motion-robust-rppg-signals","Mask Attack Detection Using Vascular-Weighted Motion-Robust rPPG Signals",[689,463,86,690,691,601],"Yao, Chenglin","Du, Heshan","Liu, Jiang","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":696,"title":697,"authors":698,"year":631,"doi":701,"venue":353,"_id":702},"\u002Fpublications\u002F2023\u002Foptimal-low-rank-qr-decomposition-with-an-application-on-rp-tsod","Optimal Low-Rank QR Decomposition with an Application on RP-TSOD",[699,463,86,700],"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":704,"title":705,"authors":706,"year":631,"doi":708,"venue":709,"_id":710},"\u002Fpublications\u002F2023\u002Fprediction-and-analysis-of-container-terminal-logistics-arrival-time-based-on-si","Prediction and Analysis of Container Terminal Logistics Arrival Time Based o",[707,101,86],"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":712,"title":713,"year":631,"doi":714,"venue":89,"_id":715},"\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-Scal","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":717,"title":718,"year":631,"doi":719,"venue":683,"_id":720},"\u002Fpublications\u002F2023\u002Fsiamese-discriminant-deep-reinforcement-learning-for-solving-jigsaw-puzzles-with","Siamese-Discriminant Deep Reinforcement Learning for Solving Jigsaw Puzzles with","https:\u002F\u002Fdoi.org\u002F10.1609\u002Faaai.v37i2.25325","content:publications:2023:siamese-discriminant-deep-reinforcement-learning-for-solving-jigsaw-puzzles-with.md",{"_path":722,"title":723,"authors":724,"year":631,"doi":730,"venue":731,"_id":732},"\u002Fpublications\u002F2023\u002Fstructural-priors-guided-network-for-the-corneal-endothelial-cell-segmentation","Structural Priors Guided Network for the Corneal Endothelial Cell Segmentation",[725,726,727,728,86,729,691],"Zhang, Yinglin","Xi, Ruiling","Zeng, Lingxi","Towey, Dave","Higashita, Risa","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":734,"title":735,"year":631,"doi":736,"venue":89,"_id":737},"\u002Fpublications\u002F2023\u002Fug-net-corneal-endothelial-cell-segmentation-based-on-uncertainty-estimation-and","UG-Net: Corneal Endothelial Cell Segmentation Based on Uncertainty Estimatio","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":739,"title":740,"year":741,"doi":742,"venue":145,"_id":743},"\u002Fpublications\u002F2024\u002Fa-cascaded-retrieval-while-reasoning-multi-document-comprehension-framework-with","A cascaded retrieval-while-reasoning multi-document comprehension framework with",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":745,"title":746,"year":741,"doi":747,"venue":89,"_id":748},"\u002Fpublications\u002F2024\u002Fa-hierarchical-cooperative-genetic-programming-for-complex-piecewise-symbolic-re","A Hierarchical Cooperative Genetic Programming for Complex Piecewise Symbolic","https:\u002F\u002Fdoi.org\u002F10.1109\u002Fcec60901.2024.10611754","content:publications:2024:a-hierarchical-cooperative-genetic-programming-for-complex-piecewise-symbolic-re.md",{"_path":750,"title":751,"year":741,"doi":752,"venue":145,"_id":753},"\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","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":755,"title":756,"year":741,"doi":757,"venue":758,"_id":759},"\u002Fpublications\u002F2024\u002Fadvancing-container-port-traffic-simulation-a-data-driven-machine-learning-appro","Advancing container port traffic simulation: A data-driven machine learnin","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":761,"title":762,"authors":763,"year":741,"doi":771,"venue":772,"_id":773},"\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",[764,765,766,767,768,86,769,770],"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":775,"title":776,"authors":777,"year":741,"doi":780,"venue":89,"_id":781},"\u002Fpublications\u002F2024\u002Fcharacterising-deep-learning-loss-landscapes-with-local-optima-networks","Characterising Deep Learning Loss Landscapes with Local Optima Networks",[778,779,86],"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":783,"title":784,"year":741,"doi":785,"venue":117,"_id":786},"\u002Fpublications\u002F2024\u002Fdeep-reinforcement-learning-assisted-genetic-programming-ensemble-hyper-heuristi","Deep Reinforcement Learning Assisted Genetic Programming Ensemble","https:\u002F\u002Fdoi.org\u002F10.1109\u002Ftevc.2024.3381042","content:publications:2024:deep-reinforcement-learning-assisted-genetic-programming-ensemble-hyper-heuristi.md",{"_path":788,"title":789,"year":741,"doi":790,"venue":791,"_id":792},"\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","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":794,"title":795,"year":741,"doi":796,"venue":797,"_id":798},"\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","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":800,"title":801,"year":741,"doi":802,"venue":89,"_id":803},"\u002Fpublications\u002F2024\u002Fevolution-assisted-deep-reinforcement-learning-for-fast-charging-station-coordin","Evolution-Assisted Deep Reinforcement Learning for Fast Charging Station","https:\u002F\u002Fdoi.org\u002F10.1109\u002Fcec60901.2024.10611768","content:publications:2024:evolution-assisted-deep-reinforcement-learning-for-fast-charging-station-coordin.md",{"_path":805,"title":806,"year":741,"doi":807,"venue":797,"_id":808},"\u002Fpublications\u002F2024\u002Fgase-graph-attention-sampling-with-edges-fusion-for-solving-vehicle-routing-prob","Gase: graph attention sampling with edges fusion for solving vehicle routin","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":810,"title":811,"year":741,"doi":812,"venue":89,"_id":813},"\u002Fpublications\u002F2024\u002Fhierarchical-perceptual-and-predictive-analogy-inference-network-for-abstract-vi","Hierarchical Perceptual and Predictive Analogy-Inference Network for Abstract","https:\u002F\u002Fdoi.org\u002F10.1145\u002F3664647.3681246","content:publications:2024:hierarchical-perceptual-and-predictive-analogy-inference-network-for-abstract-vi.md",{"_path":815,"title":816,"authors":817,"year":741,"doi":823,"venue":824,"_id":825},"\u002Fpublications\u002F2024\u002Flow-contrast-medical-image-segmentation-via-transformer-and-boundary-perception","Low-Contrast Medical Image Segmentation via Transformer and Boundary Perception",[725,726,818,819,820,821,728,86,822,729,691],"Wang, Wei","Li, Heng","Hu, Lingxi","Lin, Huiyan","Fu, Huazhu","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":827,"title":828,"year":741,"doi":829,"venue":145,"_id":830},"\u002Fpublications\u002F2024\u002Fmedical-chief-complaint-classification-with-hierarchical-structure-of-label-desc","Medical chief complaint classification with hierarchical structure of label","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":832,"title":833,"year":741,"doi":834,"venue":145,"_id":835},"\u002Fpublications\u002F2024\u002Fmobile-robot-sequential-decision-making-using-a-deep-reinforcement-learning-hype","Mobile robot sequential decision making using a deep reinforcement learning","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":837,"title":838,"authors":839,"year":741,"doi":841,"venue":89,"_id":842},"\u002Fpublications\u002F2024\u002Fmulti-view-spectrogram-transformer-for-respiratory-sound-classification","Multi-View Spectrogram Transformer for Respiratory Sound Classification",[540,840,463,86,601],"Yan, Yuchen","https:\u002F\u002Fdoi.org\u002F10.1109\u002Ficassp48485.2024.10445825","content:publications:2024:multi-view-spectrogram-transformer-for-respiratory-sound-classification.md",{"_path":844,"title":845,"authors":846,"year":741,"doi":849,"venue":677,"_id":850},"\u002Fpublications\u002F2024\u002Fpattern-based-learning-and-optimisation-through-pricing-for-bin-packing-problem","Pattern Based Learning and Optimisation Through Pricing for Bin Packing Problem",[546,86,847,101,848,463],"Liu, Tie‐Yan","Lin, Bingchen","https:\u002F\u002Fdoi.org\u002F10.2139\u002Fssrn.4822673","content:publications:2024:pattern-based-learning-and-optimisation-through-pricing-for-bin-packing-problem.md",{"_path":852,"title":853,"year":741,"doi":854,"venue":145,"_id":855},"\u002Fpublications\u002F2024\u002Fprogressively-orthogonally-mapped-efficientnet-for-action-recognition-on-time-ra","Progressively-orthogonally-mapped EfficientNet for action recognition on","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":857,"title":858,"year":741,"doi":859,"venue":638,"_id":860},"\u002Fpublications\u002F2024\u002Fradar-gait-recognition-using-dual-branch-swin-transformer-with-asymmetric-attent","Radar gait recognition using Dual-branch Swin Transformer with Asymmetric","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":862,"title":863,"year":741,"doi":864,"venue":683,"_id":865},"\u002Fpublications\u002F2024\u002Fscale-optimization-using-evolutionary-reinforcement-learning-for-object-detectio","Scale Optimization Using Evolutionary Reinforcement Learning for Object","https:\u002F\u002Fdoi.org\u002F10.1609\u002Faaai.v38i1.27795","content:publications:2024:scale-optimization-using-evolutionary-reinforcement-learning-for-object-detectio.md",{"_path":867,"title":868,"year":741,"doi":869,"venue":353,"_id":870},"\u002Fpublications\u002F2024\u002Ftransformer-surrogate-genetic-programming-for-dynamic-container-port-truck-dispa","Transformer Surrogate Genetic Programming for Dynamic Container Port Truck","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":872,"title":873,"year":741,"doi":874,"venue":638,"_id":875},"\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","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":877,"title":878,"year":879,"doi":880,"venue":758,"_id":881},"\u002Fpublications\u002F2025\u002Fa-particle-swarm-optimization-based-ensemble-metaheuristic-for-long-term-transmi","A particle swarm optimization-based ensemble metaheuristic for long-term",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":883,"title":884,"authors":885,"year":879,"doi":891,"venue":892,"_id":893},"\u002Fpublications\u002F2025\u002Fa-review-of-medical-text-analysis-theory-and-practice","A review of medical text analysis: Theory and practice",[886,887,86,888,889,890],"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":895,"title":896,"year":879,"doi":897,"venue":898,"_id":899},"\u002Fpublications\u002F2025\u002Fan-effective-combination-of-mechanisms-for-particle-swarm-optimization-based-ens","An effective combination of mechanisms for particle swarm optimization-based","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":901,"title":902,"year":879,"doi":903,"venue":89,"_id":904},"\u002Fpublications\u002F2025\u002Fceari-co-evolutionary-agents-for-reassembling-and-inpainting-puzzles-with-gaps-a","CEARI: Co-Evolutionary Agents for Reassembling and Inpainting Puzzles with Gap","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":906,"title":907,"year":879,"doi":908,"venue":683,"_id":909},"\u002Fpublications\u002F2025\u002Fdarr-a-dual-branch-arithmetic-regression-reasoning-framework-for-solving-machine","DARR: A Dual-Branch Arithmetic Regression Reasoning Framework for Solvin","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":911,"title":912,"year":879,"doi":913,"venue":89,"_id":914},"\u002Fpublications\u002F2025\u002Ffinemotion-a-dataset-and-benchmark-with-both-spatial-and-temporal-annotation-for","FineMotion: A Dataset and Benchmark with Both Spatial and Temporal Annotatio","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":916,"title":917,"authors":918,"year":879,"doi":925,"venue":926,"_id":927},"\u002Fpublications\u002F2025\u002Ffpga-routing-congestion-prediction-via-graph-learning-aided-conditional-gan","FPGA Routing Congestion Prediction via Graph Learning-Aided Conditional GAN",[919,920,921,922,923,700,86,924],"Yang, Qingyu","Li, Jingjin","Li, Rui","He, Yuting","Ha, Yajun","Yu, Heng","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":929,"title":930,"year":879,"doi":931,"venue":932,"_id":933},"\u002Fpublications\u002F2025\u002Fllm4netlist-llm-enabled-step-based-netlist-generation-from-natural-language-desc","LLM4Netlist: LLM-Enabled Step-Based Netlist Generation From Natural Languag","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":935,"title":936,"year":879,"doi":937,"venue":938,"_id":939},"\u002Fpublications\u002F2025\u002Fonline-bayesian-approximation-based-uncertainty-aware-model-for-ophthalmic-image","Online Bayesian Approximation Based Uncertainty Aware Model for 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Moto","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":962,"title":963,"authors":964,"year":967,"doi":968,"venue":145,"_id":969},"\u002Fpublications\u002F2026\u002Fmela-a-metacognitive-llm-driven-architecture-for-automatic-heuristic-design","MeLA: A metacognitive LLM-driven architecture for automatic heuristic design",[965,537,966,86],"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":971,"title":972,"authors":973,"year":967,"doi":975,"venue":145,"_id":976},"\u002Fpublications\u002F2026\u002Fonline-risk-aware-pattern-adjustment-for-bin-packing-problem","Online risk-aware pattern adjustment for bin packing problem",[546,974,86],"Liu, 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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":993,"title":994,"year":967,"doi":995,"venue":981,"_id":996},"\u002Fpublications\u002F2026\u002Franking-based-self-supervised-representation-learning-for-skeleton-based-action","Ranking-Based Self-Supervised Representation Learning for Skeleton-Based Action","https:\u002F\u002Fdoi.org\u002F10.1109\u002Ftmm.2026.3654466","content:publications:2026:ranking-based-self-supervised-representation-learning-for-skeleton-based-action.md",{"_path":998,"title":999,"year":967,"doi":1000,"venue":186,"_id":1001},"\u002Fpublications\u002F2026\u002Fscheduling-heuristic-learning-via-genetic-programming-for-dynamic-flexible-job-s","Scheduling Heuristic Learning via Genetic Programming for Dynamic Flexible Job","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",1786300795980]