{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,8]],"date-time":"2024-08-08T00:16:47Z","timestamp":1723076207709},"reference-count":66,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2024,8,1]],"date-time":"2024-08-01T00:00:00Z","timestamp":1722470400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2024,8,1]],"date-time":"2024-08-01T00:00:00Z","timestamp":1722470400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2024,8,1]],"date-time":"2024-08-01T00:00:00Z","timestamp":1722470400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2024,8,1]],"date-time":"2024-08-01T00:00:00Z","timestamp":1722470400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2024,8,1]],"date-time":"2024-08-01T00:00:00Z","timestamp":1722470400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2024,8,1]],"date-time":"2024-08-01T00:00:00Z","timestamp":1722470400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,8,1]],"date-time":"2024-08-01T00:00:00Z","timestamp":1722470400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100008530","name":"European Regional Development Fund","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100008530","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004731","name":"Zhejiang Province Natural Science Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100004731","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Computers & Industrial Engineering"],"published-print":{"date-parts":[[2024,8]]},"DOI":"10.1016\/j.cie.2024.110385","type":"journal-article","created":{"date-parts":[[2024,7,16]],"date-time":"2024-07-16T09:55:26Z","timestamp":1721123726000},"page":"110385","update-policy":"http:\/\/dx.doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Enhancing efficiency and interpretability: A multi-objective dispatching strategy for autonomous service vehicles in ride-hailing"],"prefix":"10.1016","volume":"194","author":[{"given":"Yuhan","family":"Guo","sequence":"first","affiliation":[]},{"given":"Wenhua","family":"Li","sequence":"additional","affiliation":[]},{"given":"Linfan","family":"Xiao","sequence":"additional","affiliation":[]},{"given":"Alok","family":"Choudhary","sequence":"additional","affiliation":[]},{"given":"Hamid","family":"Allaoui","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.cie.2024.110385_b0005","doi-asserted-by":"crossref","DOI":"10.1016\/j.cie.2023.109441","article-title":"A Multi-Layer blood supply chain configuration and optimization under uncertainty in COVID-19 pandemic","volume":"182","author":"Abdolazimi","year":"2023","journal-title":"Computers & Industrial Engineering"},{"key":"10.1016\/j.cie.2024.110385_b0010","doi-asserted-by":"crossref","unstructured":"AI-Kanj, L., J. Nascimento & W. Powell. (2020). Approximate Dynamic Programming for Planning a Ride-hailing system using autonomous fleets of electric vehicles. European Journal of Operational Research, 284(3), 1088-1106.","DOI":"10.1016\/j.ejor.2020.01.033"},{"key":"10.1016\/j.cie.2024.110385_b0015","unstructured":"Apollo. (2021). Available online. https:\/\/www.apollo.auto."},{"key":"10.1016\/j.cie.2024.110385_b0020","doi-asserted-by":"crossref","first-page":"1261","DOI":"10.1007\/s00500-021-06386-w","article-title":"An application of extended NSGA-II in interval valued multi-objective scheduling problem of crews","volume":"26","author":"Banerjee","year":"2021","journal-title":"Soft Computing"},{"key":"10.1016\/j.cie.2024.110385_b0025","doi-asserted-by":"crossref","DOI":"10.1016\/j.comnet.2020.107530","article-title":"Machine learning-based traffic prediction models for intelligent transportation systems","volume":"181","author":"Boukerche","year":"2020","journal-title":"Computer Networks"},{"key":"10.1016\/j.cie.2024.110385_b0030","doi-asserted-by":"crossref","DOI":"10.1016\/j.trc.2021.103156","article-title":"Efficient dispatching for on-demand ride services: Systematic optimization via Monte-Carlo tree search","volume":"127","author":"Chen","year":"2021","journal-title":"Transportation Research Part C: Emerging Technologies"},{"issue":"4","key":"10.1016\/j.cie.2024.110385_b0035","doi-asserted-by":"crossref","first-page":"2182","DOI":"10.1109\/TNSE.2020.2992931","article-title":"The Framework of Increasing Drivers' Income on the Online Taxi Platforms","volume":"7","author":"Chen","year":"2020","journal-title":"IEEE Transactions on Network Science and Engineering"},{"key":"10.1016\/j.cie.2024.110385_b0040","doi-asserted-by":"crossref","first-page":"196","DOI":"10.1016\/j.trb.2016.11.004","article-title":"A Statistical method for estimating predictable differences between daily traffic flow profiles","volume":"95","author":"Crawford","year":"2017","journal-title":"Transportation Research Part B: Methodological"},{"issue":"1","key":"10.1016\/j.cie.2024.110385_b0045","doi-asserted-by":"crossref","first-page":"378","DOI":"10.1016\/j.ejor.2021.10.012","article-title":"On the Shapley value of liability games","volume":"300","author":"Cs\u00f3ka","year":"2021","journal-title":"European Journal of Operational Research"},{"issue":"2","key":"10.1016\/j.cie.2024.110385_b0050","doi-asserted-by":"crossref","first-page":"182","DOI":"10.1109\/4235.996017","article-title":"A fast and elitist multiobjective genetic algorithm: NSGA-II","volume":"6","author":"Deb","year":"2002","journal-title":"IEEE Transactions on Evolutionary Computation"},{"key":"10.1016\/j.cie.2024.110385_b0055","unstructured":"Didi Chuxing. (2015). Available online. http:\/\/www.didichuxing.com."},{"issue":"2","key":"10.1016\/j.cie.2024.110385_b0060","doi-asserted-by":"crossref","first-page":"828","DOI":"10.1016\/j.ejor.2022.06.050","article-title":"Multi-depot electric vehicle scheduling in in-plant production logistics considering non-linear charging models","volume":"306","author":"Diefenbach","year":"2023","journal-title":"European Journal of Operational Research"},{"issue":"5","key":"10.1016\/j.cie.2024.110385_b0065","doi-asserted-by":"crossref","first-page":"2925","DOI":"10.3390\/ijerph19052925","article-title":"Predicting and analyzing road traffic injury severity using boosting-based ensemble learning models with SHAPley additive explanations","volume":"19","author":"Dong","year":"2022","journal-title":"International Journal of Environmental Research and Public Health"},{"key":"10.1016\/j.cie.2024.110385_b0070","doi-asserted-by":"crossref","first-page":"222","DOI":"10.1016\/j.cie.2019.02.032","article-title":"A column generation algorithm for vehicle scheduling and routing problems","volume":"130","author":"Faiz","year":"2019","journal-title":"Computers & Industrial Engineering"},{"issue":"14","key":"10.1016\/j.cie.2024.110385_b0075","doi-asserted-by":"crossref","first-page":"180","DOI":"10.1016\/j.neucom.2023.01.009","article-title":"\u0394free-LSTM: An error distribution free deep learning for short-term traffic flow forecasting","volume":"526","author":"Fang","year":"2023","journal-title":"Neurocomputing"},{"key":"10.1016\/j.cie.2024.110385_b0080","unstructured":"Ferov, M., & Modr\u00fd, M. (2016). Enhancing lambdamart using oblivious trees. arxiv preprint arxiv:1609.05610."},{"key":"10.1016\/j.cie.2024.110385_b0085","doi-asserted-by":"crossref","unstructured":"Gkiotsalitis, K. C. Iliopoulou & K. Kepaptsoglou. (2022). An exact approach for the multi-depot electric bus scheduling problem with time windows. European Journal of Operational Research, 306(1), 189-206.","DOI":"10.1016\/j.ejor.2022.07.017"},{"issue":"10","key":"10.1016\/j.cie.2024.110385_b0090","doi-asserted-by":"crossref","first-page":"3690","DOI":"10.1080\/00207543.2023.2247092","article-title":"A prediction-based iterative Kuhn-Munkres approach for service vehicle reallocation in ride-hailing","volume":"62","author":"Guo","year":"2024","journal-title":"International Journal of Production Research"},{"issue":"2","key":"10.1016\/j.cie.2024.110385_b0095","doi-asserted-by":"crossref","first-page":"577","DOI":"10.1016\/j.ejor.2022.04.035","article-title":"Modelling and analysis of online ride-sharing platforms \u2013 A sustainability perspective","volume":"304","author":"Guo","year":"2023","journal-title":"European Journal of Operational Research"},{"key":"10.1016\/j.cie.2024.110385_b0100","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1016\/j.trb.2021.05.015","article-title":"Robust matching-integrated vehicle rebalancing in ride-hailing system with uncertain demand","volume":"150","author":"Guo","year":"2021","journal-title":"Transportation Research Part B: Methodological"},{"issue":"3","key":"10.1016\/j.cie.2024.110385_b0105","doi-asserted-by":"crossref","first-page":"2259009.1","DOI":"10.1142\/S0218001422590091","article-title":"An improved A-star algorithm for complete coverage path planning of unmanned ships","volume":"36","author":"Guo","year":"2022","journal-title":"International Journal of Pattern Recognition and Artificial Intelligence"},{"key":"10.1016\/j.cie.2024.110385_b0110","first-page":"1090","article-title":"Deep reinforcement learning for multi-driver vehicle dispatching and repositioning problem","author":"Holler","year":"2021","journal-title":"IEEE International Conference on Data Mining"},{"key":"10.1016\/j.cie.2024.110385_b0115","first-page":"119","article-title":"Research on spatial differentiation characteristics of urban taxi trip trajectory network","volume":"1","author":"Hu","year":"2021","journal-title":"Statistics & Information Forum"},{"issue":"2","key":"10.1016\/j.cie.2024.110385_b0120","doi-asserted-by":"crossref","first-page":"581","DOI":"10.1109\/JIOT.2017.2716114","article-title":"Data driven congestion trends prediction of urban transportation","volume":"5","author":"Jia","year":"2018","journal-title":"IEEE Internet of Things Journal"},{"issue":"04","key":"10.1016\/j.cie.2024.110385_b0125","first-page":"108","article-title":"Regional mining of urban residents\u2019 travel demand based on taxi order trajectory data","volume":"42","author":"Jiao","year":"2022","journal-title":"Journal of Chang\u2019an University (Natural Science Edition)"},{"issue":"1","key":"10.1016\/j.cie.2024.110385_b0130","doi-asserted-by":"crossref","first-page":"201","DOI":"10.1016\/j.ejor.2022.02.021","article-title":"Interrelated trips in the rural dial-a-ride problem with autonomous vehicles","volume":"303","author":"Johnsen","year":"2022","journal-title":"European Journal of Operational Research"},{"key":"10.1016\/j.cie.2024.110385_b0135","doi-asserted-by":"crossref","DOI":"10.1016\/j.trc.2023.104410","article-title":"Improving deep-learning methods for area-based traffic demand prediction via hierarchical reconciliation","volume":"159","author":"Khalesian","year":"2024","journal-title":"Transportation Research Part C: Emerging Technologies"},{"issue":"7","key":"10.1016\/j.cie.2024.110385_b0140","doi-asserted-by":"crossref","first-page":"4164","DOI":"10.3390\/su14074164","article-title":"Traffic flow prediction: An intelligent scheme for forecasting traffic flow using air pollution data in smart cities with bagging ensemble","volume":"14","author":"Khan","year":"2022","journal-title":"Sustainability"},{"key":"10.1016\/j.cie.2024.110385_b0145","doi-asserted-by":"crossref","unstructured":"Lei., W.H., L. Alves & L. Amaral. (2022). Forecasting the evolution of fast-changing transportation networks using machine learning. Nature Communications, 13, 4252.","DOI":"10.1038\/s41467-022-31911-2"},{"key":"10.1016\/j.cie.2024.110385_b0150","unstructured":"Li, Y. G., R. Yu, C. Shahabi & Y. Liu. (2018). Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting. International Conference of Learning Representation."},{"issue":"3","key":"10.1016\/j.cie.2024.110385_b0155","doi-asserted-by":"crossref","first-page":"251","DOI":"10.1016\/j.clsr.2019.02.005","article-title":"A reflection on the taxi reform in China: Innovation vs Tradition","volume":"35","author":"Li","year":"2019","journal-title":"Computer Law & Security Review"},{"issue":"5","key":"10.1016\/j.cie.2024.110385_b0160","doi-asserted-by":"crossref","first-page":"5282","DOI":"10.1109\/TITS.2023.3237387","article-title":"Temporal data scheduling in internet of vehicles using an improved decomposition-based multi-objective evolutionary algorithm","volume":"24","author":"Li","year":"2023","journal-title":"IEEE Transactions on Intelligent Transportation Systems"},{"key":"10.1016\/j.cie.2024.110385_b0165","first-page":"986","article-title":"Research on vehicle dispatch problem based on kuhn-munkres and reinforcement learning algorithm","author":"Li","year":"2021","journal-title":"IEEE International Conference on Power Electronics, Computer Applications"},{"key":"10.1016\/j.cie.2024.110385_b0170","doi-asserted-by":"crossref","DOI":"10.1016\/j.tre.2022.102694","article-title":"Deep dispatching: A deep reinforcement learning approach for vehicle dispatching on online ride-hailing platform","volume":"161","author":"Liu","year":"2022","journal-title":"Transportation Research Part E: Logistics and Transportation Review"},{"key":"10.1016\/j.cie.2024.110385_b0175","doi-asserted-by":"crossref","unstructured":"Liu, Y., C. L, A. Khadka, W. Zhang & Z. Liu. (2020). Spatio-Temporal Ensemble Method for Car-Hailing Demand Prediction. IEEE Transactions on Intelligent Transportation Systems, 21(12), 5328-5333.","DOI":"10.1109\/TITS.2019.2948790"},{"issue":"11","key":"10.1016\/j.cie.2024.110385_b0180","doi-asserted-by":"crossref","first-page":"3319","DOI":"10.1080\/00207543.2021.1919780","article-title":"Level-based multi-objective particle swarm optimizer for integrated production scheduling and vehicle routing decision with inventory holding, delivery, and tardiness costs","volume":"60","author":"Long","year":"2021","journal-title":"International Journal of Production Research"},{"issue":"2","key":"10.1016\/j.cie.2024.110385_b0185","doi-asserted-by":"crossref","first-page":"419","DOI":"10.1016\/j.ejor.2020.12.021","article-title":"Metaheuristics for the online printing shop scheduling problem","volume":"293","author":"Lunardi","year":"2021","journal-title":"European Journal of Operational Research"},{"key":"10.1016\/j.cie.2024.110385_b0190","doi-asserted-by":"crossref","DOI":"10.1016\/j.tre.2021.102530","article-title":"Vehicle scheduling for rental-with-driver services","volume":"156","author":"Mancini","year":"2021","journal-title":"Transportation Research Part E: Logistics and Transportation Review"},{"key":"10.1016\/j.cie.2024.110385_b0195","doi-asserted-by":"crossref","unstructured":"Momin, K. A., S. Barua, M. Jamil & O. Hamim. (2022). Short Duration Traffic Flow Prediction Using Kalman Filtering. arXiv:2208.03415.","DOI":"10.1063\/5.0129721"},{"key":"10.1016\/j.cie.2024.110385_b0200","unstructured":"Placek, M. (2023). Number of autonomous vehicles globally 2022-2030. https:\/\/www.statista.com\/statistics\/1230664\/projected-number-autonomous-cars-worldwide\/."},{"key":"10.1016\/j.cie.2024.110385_b0205","unstructured":"Prokhorenkova, L., G. Gusev, A. Vorobev, A. Dorogush & A. Gulin. (2019). CatBoost: unbiased boosting with categorical features. arXiv:1706.09516."},{"issue":"13\u201315","key":"10.1016\/j.cie.2024.110385_b0210","doi-asserted-by":"crossref","first-page":"2331","DOI":"10.1016\/j.neucom.2005.12.132","article-title":"CATS benchmark time series prediction by Kalman smoother with cross-validated noise density","volume":"70","author":"S\u00e4rkk\u00e4","year":"2007","journal-title":"Neurocomputing"},{"issue":"1","key":"10.1016\/j.cie.2024.110385_b0215","doi-asserted-by":"crossref","first-page":"263","DOI":"10.1016\/j.ejor.2021.07.054","article-title":"Vehicle dispatching plan for minimizing passenger waiting time in a corridor with buses of different sizes: Model formulation and solution approaches","volume":"299","author":"Sadrani","year":"2022","journal-title":"European Journal of Operational Research"},{"issue":"2","key":"10.1016\/j.cie.2024.110385_b0220","doi-asserted-by":"crossref","first-page":"571","DOI":"10.1016\/j.ejor.2021.08.014","article-title":"The parallel drone scheduling problem with multiple drones and vehicles","volume":"300","author":"Saleu","year":"2021","journal-title":"European Journal of Operational Research"},{"key":"10.1016\/j.cie.2024.110385_b0225","unstructured":"Sandhaus. H., W. Ju & Q. Yang. (2023). Towards Prototyping Driverless Vehicle Behaviors, City Design, and Policies Simultaneously. arxiv-2304.06639."},{"year":"1995","series-title":"Fault tolerant design using single and multicriteria genetic algorithm optimization\u201d","author":"Schott","key":"10.1016\/j.cie.2024.110385_b0230"},{"key":"10.1016\/j.cie.2024.110385_b0235","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2024.107954","article-title":"A vehicle value based ride-hailing order matching and dispatching algorithm","volume":"132","author":"Shi","year":"2024","journal-title":"Engineering Applications of Artificial Intelligence"},{"issue":"9","key":"10.1016\/j.cie.2024.110385_b0240","doi-asserted-by":"crossref","first-page":"16654","DOI":"10.1109\/TITS.2021.3094659","article-title":"A short-term traffic flow prediction model based on an improved gate recurrent unit neural network","volume":"23","author":"Shu","year":"2021","journal-title":"IEEE Transactions on Intelligent Transportation Systems"},{"key":"10.1016\/j.cie.2024.110385_b0245","doi-asserted-by":"crossref","DOI":"10.1109\/TKDE.2023.3348491","article-title":"Optimizing long-term efficiency and fairness in ride-hailing under budget constraint via joint order dispatching and driver repositioning","author":"Sun","year":"2024","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"10.1016\/j.cie.2024.110385_b0250","unstructured":"Uber. (2009). Available online. https:\/\/www.uber.com."},{"key":"10.1016\/j.cie.2024.110385_b0255","first-page":"1","article-title":"Traditional taxi, e-hailing or ride-hailing? A GSEM approach to exploring service adoption patterns","author":"Vega-Gonzalo","year":"2023","journal-title":"Transportation"},{"key":"10.1016\/j.cie.2024.110385_b0260","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1016\/j.trb.2019.07.009","article-title":"Ride sourcing systems: A framework and review","volume":"129","author":"Wang","year":"2019","journal-title":"Transportation Research Part B: Methodological"},{"key":"10.1016\/j.cie.2024.110385_b0265","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.ins.2020.05.082","article-title":"An improved MOEA\/D algorithm with an adaptive evolutionary strategy","volume":"539","author":"Wang","year":"2020","journal-title":"Information Sciences"},{"key":"10.1016\/j.cie.2024.110385_b0270","unstructured":"Waymo. (2022). Available online. https:\/\/www.waymo.com."},{"key":"10.1016\/j.cie.2024.110385_b0275","doi-asserted-by":"crossref","first-page":"8879","DOI":"10.1007\/s10489-022-03966-7","article-title":"Urban ride-hailing demand prediction with multi-view information fusion deep learning framework","volume":"53","author":"Wu","year":"2022","journal-title":"Applied Intelligence"},{"key":"10.1016\/j.cie.2024.110385_b0280","first-page":"1907","article-title":"Graph WaveNet for deep spatial-temporal graph modeling","author":"Wu","year":"2019","journal-title":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence"},{"issue":"8","key":"10.1016\/j.cie.2024.110385_b0285","doi-asserted-by":"crossref","first-page":"13094","DOI":"10.1109\/TITS.2021.3119662","article-title":"Deep reinforcement learning with graph representation for vehicle repositioning","volume":"23","author":"Yu","year":"2021","journal-title":"IEEE Transactions on Intelligent Transportation Systems"},{"key":"10.1016\/j.cie.2024.110385_b0290","doi-asserted-by":"crossref","DOI":"10.1016\/j.cor.2022.105698","article-title":"A novel multi-objective green vehicle routing and scheduling model with stochastic demand, supply, and variable travel times","volume":"141","author":"Zarouk","year":"2022","journal-title":"Computers & Operations Research"},{"key":"10.1016\/j.cie.2024.110385_b0295","doi-asserted-by":"crossref","first-page":"3827","DOI":"10.1007\/s10489-018-1181-7","article-title":"A multivariate short-term traffic flow forecasting method based on wavelet analysis and seasonal time series","volume":"48","author":"Zhang","year":"2018","journal-title":"Applied Intelligence"},{"issue":"9","key":"10.1016\/j.cie.2024.110385_b0300","doi-asserted-by":"crossref","first-page":"16715","DOI":"10.1109\/TITS.2021.3131248","article-title":"A diverse ensemble deep learning method for short-term traffic flow prediction based on spatiotemporal correlations","volume":"23","author":"Zhang","year":"2021","journal-title":"IEEE Transactions on Intelligent Transportation Systems"},{"key":"10.1016\/j.cie.2024.110385_b0305","doi-asserted-by":"crossref","DOI":"10.1016\/j.aap.2023.107072","article-title":"A proactive crash risk prediction framework for lane-changing behavior incorporating individual driving styles","volume":"188","author":"Zhang","year":"2023","journal-title":"Accident Analysis & Prevention"},{"journal-title":"IEEE Transactions on Intelligent Transportation Systems","article-title":"Learned unmanned vehicle scheduling for large-scale urban logistics","year":"2024","author":"Zhang","key":"10.1016\/j.cie.2024.110385_b0310"},{"issue":"1","key":"10.1016\/j.cie.2024.110385_b0315","doi-asserted-by":"crossref","first-page":"2018643","DOI":"10.1080\/08839514.2021.2018643","article-title":"Prediction in traffic accident duration based on heterogeneous ensemble learning","volume":"36","author":"Zhao","year":"2022","journal-title":"Applied Artificial Intelligence"},{"key":"10.1016\/j.cie.2024.110385_b0320","doi-asserted-by":"crossref","DOI":"10.1016\/j.ijpe.2021.108301","article-title":"On-demand ride-hailing platforms in competition with the taxi industry: Pricing strategies and government supervision","volume":"243","author":"Zhong","year":"2022","journal-title":"International Journal of Production Economics"},{"year":"2021","series-title":"Machine learning","author":"Zhou","key":"10.1016\/j.cie.2024.110385_b0325"},{"issue":"4","key":"10.1016\/j.cie.2024.110385_b0330","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1109\/4235.797969","article-title":"Multi objective evolutionary algorithms: A comparative case study and the strength pareto approach","volume":"3","author":"Zitzler","year":"1999","journal-title":"IEEE Transactions on Evolutionary Computation"}],"container-title":["Computers & Industrial Engineering"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0360835224005060?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0360835224005060?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2024,8,7]],"date-time":"2024-08-07T17:16:01Z","timestamp":1723050961000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0360835224005060"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8]]},"references-count":66,"alternative-id":["S0360835224005060"],"URL":"https:\/\/doi.org\/10.1016\/j.cie.2024.110385","relation":{},"ISSN":["0360-8352"],"issn-type":[{"type":"print","value":"0360-8352"}],"subject":[],"published":{"date-parts":[[2024,8]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Enhancing efficiency and interpretability: A multi-objective dispatching strategy for autonomous service vehicles in ride-hailing","name":"articletitle","label":"Article Title"},{"value":"Computers & Industrial Engineering","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.cie.2024.110385","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2024 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"110385"}}