{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,13]],"date-time":"2026-03-13T11:38:30Z","timestamp":1773401910995,"version":"3.50.1"},"reference-count":51,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["42471462"],"award-info":[{"award-number":["42471462"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["13901-41211D-22002"],"award-info":[{"award-number":["13901-41211D-22002"]}],"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, Environment and Urban Systems"],"published-print":{"date-parts":[[2026,6]]},"DOI":"10.1016\/j.compenvurbsys.2026.102415","type":"journal-article","created":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T20:29:09Z","timestamp":1772137749000},"page":"102415","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["A multi-objective graph reinforcement learning framework for urban public facility location problem"],"prefix":"10.1016","volume":"126","author":[{"given":"Zhong","family":"Wang","sequence":"first","affiliation":[]},{"given":"Kai","family":"Cao","sequence":"additional","affiliation":[]},{"given":"Bo","family":"Huang","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"issue":"5","key":"10.1016\/j.compenvurbsys.2026.102415_bb0005","doi-asserted-by":"crossref","first-page":"903","DOI":"10.1007\/s11590-015-0968-2","article-title":"Equality measures properties for location problems","volume":"10","author":"Barbati","year":"2016","journal-title":"Optimization Letters"},{"key":"10.1016\/j.compenvurbsys.2026.102415_bb0010","series-title":"Pd-morl: Preference-driven multi-objective reinforcement learning algorithm","author":"Basaklar","year":"2022"},{"issue":"2","key":"10.1016\/j.compenvurbsys.2026.102415_bb0015","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1287\/trsc.24.2.137","article-title":"Equity maximizing facility location schemes","volume":"24","author":"Berman","year":"1990","journal-title":"Transportation Science"},{"key":"10.1016\/j.compenvurbsys.2026.102415_bb0020","doi-asserted-by":"crossref","DOI":"10.1016\/j.jag.2024.103832","article-title":"Revisiting spatial optimization in the era of geospatial big data and GeoAI","volume":"129","author":"Cao","year":"2024","journal-title":"International Journal of Applied Earth Observation Geoinformation"},{"key":"10.1016\/j.compenvurbsys.2026.102415_bb0025","series-title":"Rethinking neural multi-objective combinatorial optimization via neat weight embedding. Paper presented at the The Thirteenth International Conference on Learning (Representations)","author":"Chen","year":"2025"},{"key":"10.1016\/j.compenvurbsys.2026.102415_bb0030","first-page":"39176","article-title":"Neural multi-objective combinatorial optimization with diversity enhancement","volume":"36","author":"Chen","year":"2023","journal-title":"Advances in Neural Information Processing Systems"},{"issue":"5","key":"10.1016\/j.compenvurbsys.2026.102415_bb0035","doi-asserted-by":"crossref","first-page":"631","DOI":"10.1080\/08959420.2019.1704132","article-title":"Process and structure: Service satisfaction and recommendation in a community-based elderly meal service in Shanghai","volume":"35","author":"Chen","year":"2023","journal-title":"Journal of Aging & Social Policy"},{"key":"10.1016\/j.compenvurbsys.2026.102415_bb0040","doi-asserted-by":"crossref","DOI":"10.1016\/j.jag.2023.103526","article-title":"An attention model with multiple decoders for solving p-Center problems","volume":"125","author":"Chen","year":"2023","journal-title":"International Journal of Applied Earth Observation and Geoinformation"},{"issue":"2","key":"10.1016\/j.compenvurbsys.2026.102415_bb0045","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.compenvurbsys.2026.102415_bb0050","series-title":"Paper presented at the Proceedings of the IEEE conference on computer vision and pattern recognition","article-title":"Deep residual learning for image recognition","author":"He","year":"2016"},{"issue":"1","key":"10.1016\/j.compenvurbsys.2026.102415_bb0055","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1016\/S0377-2217(98)00039-3","article-title":"Exact solution methods for uncapacitated location problems with convex transportation costs","volume":"114","author":"Holmberg","year":"1999","journal-title":"European Journal of Operational Research"},{"key":"10.1016\/j.compenvurbsys.2026.102415_bb0060","series-title":"Paper presented at the International conference on machine learning","article-title":"Batch normalization: Accelerating deep network training by reducing internal covariate shift","author":"Ioffe","year":"2015"},{"key":"10.1016\/j.compenvurbsys.2026.102415_bb0065","series-title":"Adam: A method for stochastic optimization","author":"Kingma","year":"2014"},{"key":"10.1016\/j.compenvurbsys.2026.102415_bb0070","doi-asserted-by":"crossref","first-page":"975","DOI":"10.1007\/BF01009452","article-title":"Optimization by simulated annealing: Quantitative studies","volume":"34","author":"Kirkpatrick","year":"1984","journal-title":"Journal of Statistical Physics"},{"key":"10.1016\/j.compenvurbsys.2026.102415_bb0075","series-title":"Attention, learn to solve routing problems!","author":"Kool","year":"2018"},{"issue":"4","key":"10.1016\/j.compenvurbsys.2026.102415_bb0080","doi-asserted-by":"crossref","first-page":"699","DOI":"10.1287\/opre.14.4.699","article-title":"Branch-and-bound methods: A survey","volume":"14","author":"Lawler","year":"1966","journal-title":"Operations Research"},{"key":"10.1016\/j.compenvurbsys.2026.102415_bb0085","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1016\/j.neucom.2022.08.005","article-title":"Solve routing problems with a residual edge-graph attention neural network","volume":"508","author":"Lei","year":"2022","journal-title":"Neurocomputing"},{"issue":"2","key":"10.1016\/j.compenvurbsys.2026.102415_bb0090","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1080\/13658816.2023.2279975","article-title":"A reinforcement learning-based routing algorithm for large street networks","volume":"38","author":"Li","year":"2024","journal-title":"International Journal of Geographical Information Science"},{"issue":"6","key":"10.1016\/j.compenvurbsys.2026.102415_bb0095","doi-asserted-by":"crossref","first-page":"3103","DOI":"10.1109\/TCYB.2020.2977661","article-title":"Deep reinforcement learning for multiobjective optimization","volume":"51","author":"Li","year":"2020","journal-title":"IEEE Transactions on Cybernetics"},{"issue":"1","key":"10.1016\/j.compenvurbsys.2026.102415_bb0100","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1080\/13658816.2024.2413394","article-title":"A hierarchical deep reinforcement learning method for solving urban route planning problems under large-scale customers and real-time traffic conditions","volume":"39","author":"Li","year":"2025","journal-title":"International Journal of Geographical Information Science"},{"key":"10.1016\/j.compenvurbsys.2026.102415_bb0105","article-title":"Combinatorial optimization with graph convolutional networks and guided tree search","volume":"31","author":"Li","year":"2018","journal-title":"Advances in Neural Information Processing Systems"},{"issue":"1","key":"10.1016\/j.compenvurbsys.2026.102415_bb0110","doi-asserted-by":"crossref","DOI":"10.1080\/17538947.2023.2299211","article-title":"Sponet: Solve spatial optimization problem using deep reinforcement learning for urban spatial decision analysis","volume":"17","author":"Liang","year":"2024","journal-title":"International Journal of Digital Earth"},{"key":"10.1016\/j.compenvurbsys.2026.102415_bb0115","series-title":"Pareto set learning for neural multi-objective combinatorial optimization","author":"Lin","year":"2022"},{"key":"10.1016\/j.compenvurbsys.2026.102415_bb0120","series-title":"Paper presented at the proceedings of the AAAI conference on artificial intelligence","article-title":"Pareto set learning for multi-objective reinforcement learning","author":"Liu","year":"2025"},{"issue":"2","key":"10.1016\/j.compenvurbsys.2026.102415_bb0125","doi-asserted-by":"crossref","first-page":"226","DOI":"10.1109\/TEVC.2017.2704118","article-title":"On Tchebycheff decomposition approaches for multiobjective evolutionary optimization","volume":"22","author":"Ma","year":"2017","journal-title":"IEEE Transactions on Evolutionary Computation"},{"issue":"5","key":"10.1016\/j.compenvurbsys.2026.102415_bb0130","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1007\/BF02026822","article-title":"The variance equity measure in locational decision theory","volume":"6","author":"Maimon","year":"1986","journal-title":"Annals of Operations Research"},{"issue":"1","key":"10.1016\/j.compenvurbsys.2026.102415_bb0135","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/0377-2217(94)90200-3","article-title":"Equity measurement in facility location analysis: A review and framework","volume":"74","author":"Marsh","year":"1994","journal-title":"European Journal of Operational Research"},{"key":"10.1016\/j.compenvurbsys.2026.102415_bb0140","series-title":"Multi-objective deep reinforcement learning","author":"Mossalam","year":"2016"},{"issue":"4","key":"10.1016\/j.compenvurbsys.2026.102415_bb0145","doi-asserted-by":"crossref","first-page":"345","DOI":"10.1111\/j.1435-5597.1991.tb01737.x","article-title":"Equality measures and facility location","volume":"70","author":"Mulligan","year":"1991","journal-title":"Papers in Regional Science"},{"issue":"1","key":"10.1016\/j.compenvurbsys.2026.102415_bb0150","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1007\/s10479-007-0234-9","article-title":"Inequality measures and equitable locations","volume":"167","author":"Ogryczak","year":"2009","journal-title":"Annals of Operations Research"},{"issue":"1","key":"10.1016\/j.compenvurbsys.2026.102415_bb0155","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1068\/a220039","article-title":"The location of fire stations in a rural environment: A case study","volume":"22","author":"Richard","year":"1990","journal-title":"Environment and Planning A"},{"key":"10.1016\/j.compenvurbsys.2026.102415_bb0160","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1613\/jair.3987","article-title":"A survey of multi-objective sequential decision-making","volume":"48","author":"Roijers","year":"2013","journal-title":"Journal of Artificial Intelligence Research"},{"key":"10.1016\/j.compenvurbsys.2026.102415_bb0165","series-title":"Paper presented at the AAMAS\u201914: Proceedings of the 2014 international conference on autonomous agents & multiagent systems","article-title":"Linear support for multi-objective coordination graphs","author":"Roijers","year":"2014"},{"issue":"4","key":"10.1016\/j.compenvurbsys.2026.102415_bb0170","doi-asserted-by":"crossref","first-page":"500","DOI":"10.1057\/jors.2012.68","article-title":"Bicriteria efficiency\/equity hierarchical location models for public service application","volume":"64","author":"Smith","year":"2013","journal-title":"Journal of the Operational Research Society"},{"key":"10.1016\/j.compenvurbsys.2026.102415_bb0175","series-title":"Dynamic programming: Foundations and principles","author":"Sniedovich","year":"2010"},{"key":"10.1016\/j.compenvurbsys.2026.102415_bb0180","series-title":"Proceedings of the 32nd ACM international conference on advances in geographic information systems","first-page":"553","article-title":"Large-scale urban facility location selection with knowledge-informed reinforcement learning","author":"Su","year":"2024"},{"issue":"6","key":"10.1016\/j.compenvurbsys.2026.102415_bb0185","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s11704-024-40490-y","article-title":"A survey on deep learning-based algorithms for the traveling salesman problem","volume":"19","author":"Sui","year":"2025","journal-title":"Frontiers of Computer Science"},{"key":"10.1016\/j.compenvurbsys.2026.102415_bb0190","article-title":"Attention is all you need","volume":"30","author":"Vaswani","year":"2017","journal-title":"Advances in Neural Information Processing Systems"},{"issue":"2","key":"10.1016\/j.compenvurbsys.2026.102415_bb0195","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1068\/b37096","article-title":"Planning toward equal accessibility to services: A quadratic programming approach","volume":"40","author":"Wang","year":"2013","journal-title":"Environment and Planning B: Planning and Design"},{"key":"10.1016\/j.compenvurbsys.2026.102415_bb0200","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1016\/j.jtrangeo.2017.10.010","article-title":"Evaluating public transit services for operational efficiency and access equity","volume":"65","author":"Wei","year":"2017","journal-title":"Journal of Transport Geography"},{"key":"10.1016\/j.compenvurbsys.2026.102415_bb0205","series-title":"MODRL\/D-AM: Multiobjective deep reinforcement learning algorithm using decomposition and attention model for multiobjective optimization. International symposium on intelligence computation and applications","first-page":"575","author":"Wu","year":"2019"},{"key":"10.1016\/j.compenvurbsys.2026.102415_bb0210","doi-asserted-by":"crossref","DOI":"10.1016\/j.compenvurbsys.2021.101746","article-title":"A heuristic algorithm for balancing workloads in coverage modeling","volume":"92","author":"Xu","year":"2022","journal-title":"Computers, Environment and Urban Systems"},{"issue":"1","key":"10.1016\/j.compenvurbsys.2026.102415_bb0215","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1016\/j.ejor.2022.05.032","article-title":"Service allocation equity in location coverage analytics","volume":"305","author":"Xu","year":"2023","journal-title":"European Journal of Operational Research"},{"key":"10.1016\/j.compenvurbsys.2026.102415_bb0220","article-title":"A generalized algorithm for multi-objective reinforcement learning and policy adaptation","volume":"32","author":"Yang","year":"2019","journal-title":"Advances in neural information processing systems"},{"key":"10.1016\/j.compenvurbsys.2026.102415_bb0225","series-title":"2014 the third International conference on Agro-geoinformatics","first-page":"1","article-title":"Particle swarm optimization based spatial location allocation of urban parks\u2014A case study in Baoshan District, Shanghai, China","author":"Yu","year":"2014"},{"key":"10.1016\/j.compenvurbsys.2026.102415_bb0230","series-title":"Reward models in deep reinforcement learning: A survey","author":"Yu","year":"2025"},{"issue":"6","key":"10.1016\/j.compenvurbsys.2026.102415_bb0235","doi-asserted-by":"crossref","first-page":"712","DOI":"10.1109\/TEVC.2007.892759","article-title":"MOEA\/D: A multiobjective evolutionary algorithm based on decomposition","volume":"11","author":"Zhang","year":"2007","journal-title":"IEEE Transactions on Evolutionary Computation"},{"issue":"9","key":"10.1016\/j.compenvurbsys.2026.102415_bb0240","doi-asserted-by":"crossref","first-page":"748","DOI":"10.1038\/s43588-023-00503-5","article-title":"Spatial planning of urban communities via deep reinforcement learning","volume":"3","author":"Zheng","year":"2023","journal-title":"Nature Computational Science"},{"key":"10.1016\/j.compenvurbsys.2026.102415_bb0245","doi-asserted-by":"crossref","DOI":"10.1016\/j.jag.2024.103710","article-title":"ReCovNet: Reinforcement learning with covering information for solving maximal coverage billboards location problem","volume":"128","author":"Zhong","year":"2024","journal-title":"International Journal of Applied Earth Observation Geoinformation"},{"key":"10.1016\/j.compenvurbsys.2026.102415_bb0250","series-title":"2012 IEEE congress on evolutionary computation","first-page":"1","article-title":"A multiobjective evolutionary algorithm based on decomposition and probability model","author":"Zhou","year":"2012"},{"key":"10.1016\/j.compenvurbsys.2026.102415_bb0255","doi-asserted-by":"crossref","DOI":"10.1016\/j.jag.2023.103436","article-title":"Spatial multi-objective optimization of institutional elderly-care facilities: A case study in Shanghai","volume":"122","author":"Zhou","year":"2023","journal-title":"International Journal of Applied Earth Observation Geoinformation"}],"container-title":["Computers, Environment and Urban Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0198971526000177?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0198971526000177?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,3,13]],"date-time":"2026-03-13T09:22:52Z","timestamp":1773393772000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0198971526000177"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6]]},"references-count":51,"alternative-id":["S0198971526000177"],"URL":"https:\/\/doi.org\/10.1016\/j.compenvurbsys.2026.102415","relation":{},"ISSN":["0198-9715"],"issn-type":[{"value":"0198-9715","type":"print"}],"subject":[],"published":{"date-parts":[[2026,6]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"A multi-objective graph reinforcement learning framework for urban public facility location problem","name":"articletitle","label":"Article Title"},{"value":"Computers, Environment and Urban Systems","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.compenvurbsys.2026.102415","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"102415"}}