{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,5]],"date-time":"2026-09-05T05:16:56Z","timestamp":1788585416649,"version":"build-2803163510"},"reference-count":68,"publisher":"Springer Science and Business Media LLC","issue":"15","license":[{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"Scientific Research Startup Fund Project for High-level Talents of West Anhui University","award":["WGKQ2026042"],"award-info":[{"award-number":["WGKQ2026042"]}]},{"name":"Social Sciences Foundation of Anhui Province Higher School","award":["2024AH053473"],"award-info":[{"award-number":["2024AH053473"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["72171067"],"award-info":[{"award-number":["72171067"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput & Applic"],"published-print":{"date-parts":[[2026,8]]},"DOI":"10.1007\/s00521-026-12348-w","type":"journal-article","created":{"date-parts":[[2026,8,6]],"date-time":"2026-08-06T06:41:11Z","timestamp":1785998471000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Fuzzy multi-objective optimization models for provider selection and order allocation under disruptions in logistics service supply chain"],"prefix":"10.1007","volume":"38","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3109-5124","authenticated-orcid":false,"given":"Liangcheng","family":"Xu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chenglei","family":"Sun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaojian","family":"Hu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lei","family":"Yu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,8,6]]},"reference":[{"key":"12348_CR1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijpe.2025.109734","volume":"289","author":"Y Wang","year":"2025","unstructured":"Wang Y, Chen A, Liu N (2025) Constructing resilient supply chain for risk-averse buyers by data-driven robust optimization approach. Int J Prod Econ 289:109734. https:\/\/doi.org\/10.1016\/j.ijpe.2025.109734","journal-title":"Int J Prod Econ"},{"issue":"2","key":"12348_CR2","doi-asserted-by":"publisher","first-page":"421","DOI":"10.1016\/j.ejor.2025.09.032","volume":"331","author":"A De","year":"2026","unstructured":"De A, Kundu T, Sheu JB et al (2026) Proactive logistics-redistribution strategic planning in response to facility disruptions under contingencies. Eur J Oper Res 331(2):421\u2013440. https:\/\/doi.org\/10.1016\/j.ejor.2025.09.032","journal-title":"Eur J Oper Res"},{"key":"12348_CR3","doi-asserted-by":"publisher","DOI":"10.1016\/j.cie.2023.109810","author":"J Lee","year":"2023","unstructured":"Lee J, Moon I (2023) Supplier selection and order allocation problems considering regional and supplier disruptions with a risk-averse strategy. Comput Ind Eng 109810. https:\/\/doi.org\/10.1016\/j.cie.2023.109810","journal-title":"Comput Ind Eng"},{"issue":"3","key":"12348_CR4","doi-asserted-by":"publisher","first-page":"1365","DOI":"10.1016\/j.ejor.2022.11.021","volume":"308","author":"M Zheng","year":"2023","unstructured":"Zheng M, Dong S, Zhou Y et al (2023) Sourcing decisions with uncertain time-dependent supply from an unreliable supplier. Eur J Oper Res 308(3):1365\u20131379. https:\/\/doi.org\/10.1016\/j.ejor.2022.11.021","journal-title":"Eur J Oper Res"},{"key":"12348_CR5","doi-asserted-by":"publisher","first-page":"57","DOI":"10.1016\/j.indmarman.2021.11.015","volume":"101","author":"X Yan","year":"2022","unstructured":"Yan X, Liu W, Lim MK et al (2022) Exploring the factors to promote circular supply chain implementation in the smart logistics ecological chain. Ind Mark Manage 101:57\u201370. https:\/\/doi.org\/10.1016\/j.indmarman.2021.11.015","journal-title":"Ind Mark Manage"},{"key":"12348_CR6","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2023.121387","volume":"237","author":"L Xu","year":"2024","unstructured":"Xu L, Hu X, Zhang Y et al (2024) A fuzzy multiobjective team decision model for codp and supplier selection in customized logistics service supply chain. Expert Syst Appl 237:121387. https:\/\/doi.org\/10.1016\/j.eswa.2023.121387","journal-title":"Expert Syst Appl"},{"key":"12348_CR7","doi-asserted-by":"publisher","first-page":"76","DOI":"10.1016\/j.tre.2018.10.011","volume":"120","author":"X Hu","year":"2018","unstructured":"Hu X, Wang G, Li X et al (2018) Joint decision model of supplier selection and order allocation for the mass customization of logistics services. Transportation Research Part E Logistics and Transportation Review 120:76\u201395. https:\/\/doi.org\/10.1016\/j.tre.2018.10.011","journal-title":"Transportation Research Part E Logistics and Transportation Review"},{"key":"12348_CR8","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2024.107966","volume":"133","author":"A Saha","year":"2024","unstructured":"Saha A, Debnath BK, Chatterjee P et al (2024) Generalized dombi-based probabilistic hesitant fuzzy consensus reaching model for supplier selection under healthcare supply chain framework. Eng Appl Artif Intell 133:107966. https:\/\/doi.org\/10.1016\/j.engappai.2024.107966","journal-title":"Eng Appl Artif Intell"},{"key":"12348_CR9","doi-asserted-by":"publisher","DOI":"10.1016\/j.cor.2024.106532","volume":"164","author":"F Zhu","year":"2024","unstructured":"Zhu F, Pei J, Liao B et al (2024) A modified variable neighborhood search algorithm for dynamic lot-sizing with supplier selection under varying delivery time quotation. Computers & Operations Research 164:106532. https:\/\/doi.org\/10.1016\/j.cor.2024.106532","journal-title":"Computers & Operations Research"},{"key":"12348_CR10","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2023.122368","volume":"239","author":"S Song","year":"2024","unstructured":"Song S, Tappia E, Song G et al (2024) Fostering supply chain resilience for omni-channel retailers: A two-phase approach for supplier selection and demand allocation under disruption risks. Expert Syst Appl 239:122368. https:\/\/doi.org\/10.1016\/j.eswa.2023.122368","journal-title":"Expert Syst Appl"},{"key":"12348_CR11","doi-asserted-by":"publisher","DOI":"10.1007\/s10668-025-06715-1","author":"S Mazaheri","year":"2025","unstructured":"Mazaheri S, Zahedi F, Heidari A et al (2025) Material ordering and supplier selection in sustainable project scheduling: a multi-criteria decision making and mathematical modelling approach. Environ Dev Sustain. https:\/\/doi.org\/10.1007\/s10668-025-06715-1","journal-title":"Environ Dev Sustain"},{"key":"12348_CR12","doi-asserted-by":"publisher","DOI":"10.1142\/s0217595925500186","author":"M Hamidi","year":"2025","unstructured":"Hamidi M, Seifbarghy M, Yousefi M (2025) Integration of quality function deployment and MCDM techniques in a neutrosophic environment for supplier selection and evaluation. Asia-Pac J Oper Res 2550018. https:\/\/doi.org\/10.1142\/s0217595925500186","journal-title":"Asia-Pac J Oper Res"},{"key":"12348_CR13","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijpe.2022.108601","volume":"253","author":"F Wissuwa","year":"2022","unstructured":"Wissuwa F, Durach CF, Choi TY (2022) Selecting resilient suppliers: Supplier complexity and buyer disruption. Int J Prod Econ 253:108601. https:\/\/doi.org\/10.1016\/j.ijpe.2022.108601","journal-title":"Int J Prod Econ"},{"key":"12348_CR14","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2021.115129","volume":"180","author":"F Firouzi","year":"2021","unstructured":"Firouzi F, Jadidi O (2021) Multi-objective model for supplier selection and order allocation problem with fuzzy parameters. Expert Syst Appl 180:115129. https:\/\/doi.org\/10.1016\/j.eswa.2021.115129","journal-title":"Expert Syst Appl"},{"key":"12348_CR15","doi-asserted-by":"publisher","DOI":"10.1016\/j.cie.2022.108825","volume":"174","author":"S Islam","year":"2022","unstructured":"Islam S, Amin SH, Wardley LJ (2022) Supplier selection and order allocation planning using predictive analytics and multi-objective programming. Computers & Industrial Engineering 174:108825. https:\/\/doi.org\/10.1016\/j.cie.2022.108825","journal-title":"Computers & Industrial Engineering"},{"key":"12348_CR16","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2023.120119","volume":"225","author":"H Ali","year":"2023","unstructured":"Ali H, Zhang J (2023) A fuzzy multi-objective decision-making model for global green supplier selection and order allocation under quantity discounts. Expert Syst Appl 225:120119. https:\/\/doi.org\/10.1016\/j.eswa.2023.120119","journal-title":"Expert Syst Appl"},{"key":"12348_CR17","doi-asserted-by":"publisher","DOI":"10.1016\/j.cie.2023.109810","volume":"187","author":"J Lee","year":"2024","unstructured":"Lee J, Moon I (2024) Supplier selection and order allocation problems considering regional and supplier disruptions with a risk-averse strategy. Computers & Industrial Engineering 187:109810. https:\/\/doi.org\/10.1016\/j.cie.2023.109810","journal-title":"Computers & Industrial Engineering"},{"key":"12348_CR18","doi-asserted-by":"publisher","DOI":"10.1016\/j.cie.2024.110834","volume":"200","author":"D Kumar","year":"2025","unstructured":"Kumar D, Soni G, Mangla SK et al (2025) A machine learning-based hybrid approach for maximizing supply chain reliability in a pharmaceutical supply chain. Computers & Industrial Engineering 200:110834. https:\/\/doi.org\/10.1016\/j.cie.2024.110834","journal-title":"Computers & Industrial Engineering"},{"key":"12348_CR19","doi-asserted-by":"publisher","DOI":"10.1016\/j.omega.2025.103413","volume":"138","author":"G Dai","year":"2026","unstructured":"Dai G, Zhang X, Zhang RQ (2026) Two-stage robust optimization approach for supplier selection, development, and order allocation under uncertainty. Omega 138:103413. https:\/\/doi.org\/10.1016\/j.omega.2025.103413","journal-title":"Omega"},{"key":"12348_CR20","doi-asserted-by":"publisher","first-page":"50","DOI":"10.1016\/j.ijpe.2016.01.021","volume":"175","author":"W Liu","year":"2016","unstructured":"Liu W, Liang Z, Ye Z et al (2016) The optimal decision of customer order decoupling point for order insertion scheduling in logistics service supply chain. Int J Prod Econ 175:50\u201360. https:\/\/doi.org\/10.1016\/j.ijpe.2016.01.021","journal-title":"Int J Prod Econ"},{"key":"12348_CR21","doi-asserted-by":"publisher","first-page":"112","DOI":"10.1016\/j.apm.2017.09.027","volume":"54","author":"W Liu","year":"2018","unstructured":"Liu W, Wu R, Liang Z et al (2018) Decision model for the customer order decoupling point considering order insertion scheduling with capacity and time constraints in logistics service supply chain. Appl Math Model 54:112\u2013135. https:\/\/doi.org\/10.1016\/j.apm.2017.09.027","journal-title":"Appl Math Model"},{"key":"12348_CR22","doi-asserted-by":"publisher","DOI":"10.1016\/j.cie.2019.106216","volume":"140","author":"G Wang","year":"2020","unstructured":"Wang G, Hu X, Li X et al (2020) Multiobjective decisions for provider selection and order allocation considering the position of the codp in a logistics service supply chain. Computers & Industrial Engineering 140:106216. https:\/\/doi.org\/10.1016\/j.cie.2019.106216","journal-title":"Computers & Industrial Engineering"},{"issue":"02","key":"12348_CR23","doi-asserted-by":"publisher","first-page":"2250021","DOI":"10.1142\/S021759592250021X","volume":"40","author":"E Wang","year":"2022","unstructured":"Wang E, Li L, Yang K et al (2022) Integrating customer order decoupling point with operation planning in deteriorating supply chain: General dynamic model and applications. Asia-Pacific J Oper Res 40(02):2250021. https:\/\/doi.org\/10.1142\/S021759592250021X","journal-title":"Asia-Pacific J Oper Res"},{"issue":"19","key":"12348_CR24","doi-asserted-by":"publisher","first-page":"11097","DOI":"10.1007\/s00521-024-09647-5","volume":"36","author":"X Hu","year":"2024","unstructured":"Hu X, Xu L, Yao G et al (2024) Multi-codp decision models for supplier selection and order allocation in customized logistics service supply chain. Neural Comput Appl 36(19):11097\u201311119. https:\/\/doi.org\/10.1007\/s00521-024-09647-5","journal-title":"Neural Comput Appl"},{"key":"12348_CR25","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijpe.2024.109368","volume":"276","author":"R Dou","year":"2024","unstructured":"Dou R, Liu X, Lin KY et al (2024) Internal- and external-sourcing strategy analysis of group manufacturing enterprises under semiconductor supply chain disruption risk. Int J Prod Econ 276:109368. https:\/\/doi.org\/10.1016\/j.ijpe.2024.109368","journal-title":"Int J Prod Econ"},{"key":"12348_CR26","doi-asserted-by":"publisher","DOI":"10.1016\/j.tre.2024.103952","volume":"195","author":"X Shi","year":"2025","unstructured":"Shi X, Prajogo D, Fan D et al (2025) Is operational flexibility a viable strategy during major supply chain disruptions? evidence from the covid-19 pandemic. Transportation Research Part E Logistics and Transportation Review 195:103952. https:\/\/doi.org\/10.1016\/j.tre.2024.103952","journal-title":"Transportation Research Part E Logistics and Transportation Review"},{"key":"12348_CR27","doi-asserted-by":"publisher","DOI":"10.1016\/j.cie.2026.111869","volume":"214","author":"A Kumar","year":"2026","unstructured":"Kumar A, Sarmah S (2026) A multi-stage stochastic model for sustainable semiconductor manufacturing. Computers & Industrial Engineering 214:111869. https:\/\/doi.org\/10.1016\/j.cie.2026.111869","journal-title":"Computers & Industrial Engineering"},{"key":"12348_CR28","doi-asserted-by":"publisher","DOI":"10.1016\/j.omega.2024.103250","volume":"133","author":"B Niu","year":"2025","unstructured":"Niu B, Deng X, Xie F et al (2025) Dual sourcing hurts supply chain viability? the value of brand-owners cooperation under single sourcing. Omega 133:103250. https:\/\/doi.org\/10.1016\/j.omega.2024.103250","journal-title":"Omega"},{"key":"12348_CR29","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2026.131182","volume":"309","author":"P He","year":"2026","unstructured":"He P, Geng S, Chan FT et al (2026) Joint decisions of pricing and inventory of a dual-channel supply chain with demand ambiguity considering free-riding behavior under sales effort: based on a fuzzy optimization method. Expert Syst Appl 309:131182. https:\/\/doi.org\/10.1016\/j.eswa.2026.131182","journal-title":"Expert Syst Appl"},{"key":"12348_CR30","doi-asserted-by":"publisher","DOI":"10.1016\/j.tre.2025.104615","volume":"207","author":"MM Vali-Siar","year":"2026","unstructured":"Vali-Siar MM, Tikani H, Demir E et al (2026) Resilient supply chain network design under super-disruption considering inter-arrival time dependency: a new data-driven stochastic optimization approach. Transportation Research Part E Logistics and Transportation Review 207:104615. https:\/\/doi.org\/10.1016\/j.tre.2025.104615","journal-title":"Transportation Research Part E Logistics and Transportation Review"},{"issue":"1","key":"12348_CR31","doi-asserted-by":"publisher","first-page":"196","DOI":"10.2139\/ssrn.3007959","volume":"24","author":"X Shan","year":"2022","unstructured":"Shan X, Li T, Sethi SP (2022) A responsive-pricing retailer sourcing from competing suppliers facing disruptions. Manufacturing & Service Operations Management 24(1):196\u2013213. https:\/\/doi.org\/10.2139\/ssrn.3007959","journal-title":"Manufacturing & Service Operations Management"},{"key":"12348_CR32","doi-asserted-by":"publisher","DOI":"10.1016\/j.tre.2024.103723","volume":"191","author":"M Wu","year":"2024","unstructured":"Wu M, Chen J, Xue W et al (2024) Competing buyers investment and ordering strategies under supply disruption. Transportation Research Part E Logistics and Transportation Review 191:103723. https:\/\/doi.org\/10.1016\/j.tre.2024.103723","journal-title":"Transportation Research Part E Logistics and Transportation Review"},{"key":"12348_CR33","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijpe.2025.109810","author":"T De Backker","year":"2025","unstructured":"De Backker T, Vercammen A, Boute R (2025) A data-driven component risk matrix to assess supply chain disruption risk. Int J Prod Econ 109810. https:\/\/doi.org\/10.1016\/j.ijpe.2025.109810","journal-title":"Int J Prod Econ"},{"key":"12348_CR34","doi-asserted-by":"publisher","DOI":"10.1016\/j.tre.2025.104172","volume":"200","author":"M Hart Nibbrig","year":"2025","unstructured":"Hart Nibbrig M, Sharif Azadeh S, Maknoon M (2025) Adaptive resilience strategies for supply chain networks against disruptions. Transportation Research Part E Logistics and Transportation Review 200:104172. https:\/\/doi.org\/10.1016\/j.tre.2025.104172","journal-title":"Transportation Research Part E Logistics and Transportation Review"},{"key":"12348_CR35","doi-asserted-by":"publisher","DOI":"10.1016\/j.cie.2026.111824","volume":"213","author":"Y Wang","year":"2026","unstructured":"Wang Y, Liu N, Bai X (2026) Robustifying resilient supply chain against ambiguous facility disruptions under new risk-averse criteria. Computers & Industrial Engineering 213:111824. https:\/\/doi.org\/10.1016\/j.cie.2026.111824","journal-title":"Computers & Industrial Engineering"},{"key":"12348_CR36","doi-asserted-by":"publisher","DOI":"10.1016\/j.jclepro.2024.143836","volume":"478","author":"M Yavari","year":"2024","unstructured":"Yavari M, Mihankhah S, Jozani SM (2024) Assessing cap-and-trade regulation\u2019s impact on dual-channel green supply chains under disruption. J Clean Prod 478:143836. https:\/\/doi.org\/10.1016\/j.jclepro.2024.143836","journal-title":"J Clean Prod"},{"key":"12348_CR37","doi-asserted-by":"publisher","DOI":"10.1016\/j.cie.2025.111690","volume":"212","author":"H Wei","year":"2026","unstructured":"Wei H, Yu B, Yuan W (2026) A robust booking and pricing strategy for option-spot dual-channel shipping spaces considering shippers price reference effects. Computers & Industrial Engineering 212:111690. https:\/\/doi.org\/10.1016\/j.cie.2025.111690","journal-title":"Computers & Industrial Engineering"},{"key":"12348_CR38","doi-asserted-by":"publisher","DOI":"10.1016\/j.tre.2020.101838","volume":"134","author":"T Zhao","year":"2020","unstructured":"Zhao T, Xu X, Chen Y et al (2020) Coordination of a fashion supply chain with demand disruptions. Transportation Research Part E Logistics and Transportation Review 134:101838. https:\/\/doi.org\/10.1016\/j.tre.2020.101838","journal-title":"Transportation Research Part E Logistics and Transportation Review"},{"key":"12348_CR39","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijpe.2020.107830","volume":"231","author":"H Kaur","year":"2021","unstructured":"Kaur H, Singh SP (2021) Multi-stage hybrid model for supplier selection and order allocation considering disruption risks and disruptive technologies. Int J Prod Econ 231:107830. https:\/\/doi.org\/10.1016\/j.ijpe.2020.107830","journal-title":"Int J Prod Econ"},{"issue":"17","key":"12348_CR40","doi-asserted-by":"publisher","first-page":"11125","DOI":"10.1007\/s00521-020-05657-1","volume":"33","author":"C James","year":"2021","unstructured":"James C, Mondal S (2021) Optimization of decoupling point position using metaheuristic evolutionary algorithms for smart mass customization manufacturing. Neural Comput Appl 33(17):11125\u201311155. https:\/\/doi.org\/10.1007\/s00521-020-05657-1","journal-title":"Neural Comput Appl"},{"key":"12348_CR41","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2025.130833","volume":"305","author":"L Xu","year":"2026","unstructured":"Xu L, Hu X, Wu Z et al (2026) A two-stage model for logistics service provider rank and order allocation in supply chain considering digital technology empowerment. Expert Syst Appl 305:130833. https:\/\/doi.org\/10.1016\/j.eswa.2025.130833","journal-title":"Expert Syst Appl"},{"key":"12348_CR42","doi-asserted-by":"publisher","DOI":"10.1016\/j.cie.2021.107811","volume":"165","author":"ZS Hosseini","year":"2021","unstructured":"Hosseini ZS, Flapper SD, Pirayesh M (2021) Sustainable supplier selection and order allocation under demand, supplier availability and supplier grading uncertainties. Computers & Industrial Engineering 165:107811. https:\/\/doi.org\/10.1016\/j.cie.2021.107811","journal-title":"Computers & Industrial Engineering"},{"key":"12348_CR43","doi-asserted-by":"publisher","DOI":"10.1080\/00207543.2021.1924412","author":"L Cui","year":"2021","unstructured":"Cui L, Wu H, Dai J (2021) Modelling flexible decisions about sustainable supplier selection in multitier sustainable supply chain management. International Journal of Production Research. https:\/\/doi.org\/10.1080\/00207543.2021.1924412","journal-title":"International Journal of Production Research"},{"issue":"10","key":"12348_CR44","doi-asserted-by":"publisher","first-page":"23483","DOI":"10.1007\/s10668-023-03362-2","volume":"27","author":"I Shahsavani","year":"2025","unstructured":"Shahsavani I, Goli A (2025) A systematic literature review of circular supply chain network design: application of optimization models. Environ Dev Sustain 27(10):23483\u201323514. https:\/\/doi.org\/10.1007\/s10668-023-03362-2","journal-title":"Environ Dev Sustain"},{"key":"12348_CR45","doi-asserted-by":"publisher","first-page":"65","DOI":"10.1016\/j.apm.2024.05.014","volume":"133","author":"O Jadidi","year":"2024","unstructured":"Jadidi O, Cavalieri S, Firouzi F (2024) Supplier selection and order allocation problem under demand and supply uncertainty with return policy. Appl Math Model 133:65\u201378. https:\/\/doi.org\/10.1016\/j.apm.2024.05.014","journal-title":"Appl Math Model"},{"key":"12348_CR46","doi-asserted-by":"publisher","DOI":"10.1016\/j.cie.2024.110319","volume":"193","author":"R Lotfi","year":"2024","unstructured":"Lotfi R, Khanbaba A, Ali Alkhazaleh H et al (2024) A viable supplier selection with order allocation by considering robustness, risk-averse and blockchain technology. Computers & Industrial Engineering 193:110319. https:\/\/doi.org\/10.1016\/j.cie.2024.110319","journal-title":"Computers & Industrial Engineering"},{"issue":"1","key":"12348_CR47","doi-asserted-by":"publisher","first-page":"2195055","DOI":"10.1080\/23302674.2023.2195055","volume":"10","author":"A Mohammed","year":"2023","unstructured":"Mohammed A, Bai C, Channouf N et al (2023) G-resilient multi-tier supplier selection and order allocation in food industry: a hybrid methodology. International Journal of Systems Science Operations & Logistics 10(1):2195055. https:\/\/doi.org\/10.1080\/23302674.2023.2195055","journal-title":"International Journal of Systems Science Operations & Logistics"},{"key":"12348_CR48","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijpe.2020.108007","volume":"233","author":"JA Ventura","year":"2021","unstructured":"Ventura JA, Bunn KA, Venegas BB et al (2021) A coordination mechanism for supplier selection and order quantity allocation with price-sensitive demand and finite production rates. Int J Prod Econ 233:108007. https:\/\/doi.org\/10.1016\/j.ijpe.2020.108007","journal-title":"Int J Prod Econ"},{"key":"12348_CR49","doi-asserted-by":"publisher","DOI":"10.1016\/j.cor.2021.105515","volume":"137","author":"Y Sun","year":"2022","unstructured":"Sun Y, Guo SC, Li X (2022) An order-splitting model for supplier selection and order allocation in a multi-echelon supply chain. Computers & Operations Research 137:105515. https:\/\/doi.org\/10.1016\/j.cor.2021.105515","journal-title":"Computers & Operations Research"},{"key":"12348_CR50","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2023.106511","volume":"124","author":"S Nayeri","year":"2023","unstructured":"Nayeri S, Khoei MA, Rouhani-Tazangi MR et al (2023) A data-driven model for sustainable and resilient supplier selection and order allocation problem in a responsive supply chain: A case study of healthcare system. Eng Appl Artif Intell 124:106511. https:\/\/doi.org\/10.1016\/j.engappai.2023.106511","journal-title":"Eng Appl Artif Intell"},{"key":"12348_CR51","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2023.122368","volume":"239","author":"S Song","year":"2024","unstructured":"Song S, Tappia E, Song G et al (2024) Fostering supply chain resilience for omni-channel retailers: A two-phase approach for supplier selection and demand allocation under disruption risks. Expert Syst Appl 239:122368. https:\/\/doi.org\/10.1016\/j.eswa.2023.122368","journal-title":"Expert Syst Appl"},{"key":"12348_CR52","doi-asserted-by":"publisher","first-page":"1130","DOI":"10.1016\/j.apm.2020.10.024","volume":"90","author":"A Alejo-Reyes","year":"2021","unstructured":"Alejo-Reyes A, Mendoza A, Olivares-Benitez E (2021) A heuristic method for the supplier selection and order quantity allocation problem. Appl Math Model 90:1130\u20131142. https:\/\/doi.org\/10.1016\/j.apm.2020.10.024","journal-title":"Appl Math Model"},{"key":"12348_CR53","doi-asserted-by":"publisher","DOI":"10.1016\/j.aei.2023.102103","volume":"57","author":"J Jiang","year":"2023","unstructured":"Jiang J, Kong XT, Chan HK (2023) Omni-fulfillment network design for supply chain service platform considering cost, service and resilience tradeoffs. Adv Eng Inform 57:102103. https:\/\/doi.org\/10.1016\/j.aei.2023.102103","journal-title":"Adv Eng Inform"},{"key":"12348_CR54","doi-asserted-by":"publisher","DOI":"10.1016\/j.cie.2022.108825","volume":"174","author":"S Islam","year":"2022","unstructured":"Islam S, Amin SH, Wardley LJ (2022) Supplier selection and order allocation planning using predictive analytics and multi-objective programming. Computers & Industrial Engineering 174:108825. https:\/\/doi.org\/10.1016\/j.cie.2022.108825","journal-title":"Computers & Industrial Engineering"},{"key":"12348_CR55","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2023.121121","volume":"235","author":"S Islam","year":"2024","unstructured":"Islam S, Amin SH, Wardley LJ (2024) A supplier selection & order allocation planning framework by integrating deep learning, principal component analysis, and optimization techniques. Expert Syst Appl 235:121121. https:\/\/doi.org\/10.1016\/j.eswa.2023.121121","journal-title":"Expert Syst Appl"},{"issue":"1","key":"12348_CR56","doi-asserted-by":"publisher","first-page":"17388","DOI":"10.1038\/s41598-024-68449-w","volume":"14","author":"A Goli","year":"2024","unstructured":"Goli A (2024) Optimization of renewable energy project portfolio selection using hybrid ais-afs algorithm in an international case study. Sci Rep 14(1):17388. https:\/\/doi.org\/10.1038\/s41598-024-68449-w","journal-title":"Sci Rep"},{"key":"12348_CR57","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijpe.2024.109427","volume":"278","author":"A Goli","year":"2024","unstructured":"Goli A (2024b) Efficient optimization of robust project scheduling for industry 4.0: a hybrid approach based on machine learning and meta-heuristic algorithms. Int J Prod Econ 278:109427. https:\/\/doi.org\/10.1016\/j.ijpe.2024.109427","journal-title":"Int J Prod Econ"},{"issue":"36","key":"12348_CR58","doi-asserted-by":"publisher","first-page":"86268","DOI":"10.1007\/s11356-023-28044-4","volume":"30","author":"S Rahmani","year":"2023","unstructured":"Rahmani S, Goli A (2023) Robust sustainable canola oil-based biodiesel supply chain network design under supply and demand uncertainty. Environ Sci Pollut Res 30(36):86268\u201386299. https:\/\/doi.org\/10.1007\/s11356-023-28044-4","journal-title":"Environ Sci Pollut Res"},{"key":"12348_CR59","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2024.108980","volume":"136","author":"A Ala","year":"2024","unstructured":"Ala A, Goli A (2024) Incorporating machine learning and optimization techniques for assigning patients to operating rooms by considering fairness policies. Eng Appl Artif Intell 136:108980. https:\/\/doi.org\/10.1016\/j.engappai.2024.108980","journal-title":"Eng Appl Artif Intell"},{"key":"12348_CR60","doi-asserted-by":"publisher","DOI":"10.1016\/j.cie.2025.111294","volume":"207","author":"A Hosseini","year":"2025","unstructured":"Hosseini A, Goli A (2025) Energy-aware dual-channel agricultural supply chain network design under uncertainty. Computers & Industrial Engineering 207:111294. https:\/\/doi.org\/10.1016\/j.cie.2025.111294","journal-title":"Computers & Industrial Engineering"},{"key":"12348_CR61","doi-asserted-by":"publisher","first-page":"124","DOI":"10.1016\/j.ijpe.2019.03.018","volume":"213","author":"S Hosseini","year":"2019","unstructured":"Hosseini S, Morshedlou N, Ivanov D et al (2019) Resilient supplier selection and optimal order allocation under disruption risks. Int J Prod Econ 213:124\u2013137. https:\/\/doi.org\/10.1016\/j.ijpe.2019.03.018","journal-title":"Int J Prod Econ"},{"issue":"1","key":"12348_CR62","doi-asserted-by":"publisher","first-page":"2552899","DOI":"10.1080\/23302674.2025.2552899","volume":"12","author":"L Xu","year":"2025","unstructured":"Xu L, Hu X, Wu Z et al (2025) Disruption response strategy models for supplier selection and order allocation in customised logistics service supply chain. International Journal of Systems Science Operations & Logistics 12(1):2552899. https:\/\/doi.org\/10.1080\/23302674.2025.2552899","journal-title":"International Journal of Systems Science Operations & Logistics"},{"key":"12348_CR63","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2026.114743","volume":"192","author":"R Dou","year":"2026","unstructured":"Dou R, Lu Z, Wang H et al (2026) Supply chain network design considering uncertain disruption risks and carbon constraints. Appl Soft Comput 192:114743. https:\/\/doi.org\/10.1016\/j.asoc.2026.114743","journal-title":"Appl Soft Comput"},{"key":"12348_CR64","doi-asserted-by":"publisher","first-page":"49","DOI":"10.1016\/j.omega.2014.11.009","volume":"53","author":"J Rezaei","year":"2015","unstructured":"Rezaei J (2015) Best-worst multi-criteria decision-making method. Omega 53:49\u201357. https:\/\/doi.org\/10.1016\/j.omega.2014.11.009","journal-title":"Omega"},{"key":"12348_CR65","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2023.121698","volume":"238","author":"Z Wei","year":"2024","unstructured":"Wei Z, Mukherjee S (2024) Analyzing and forecasting service demands using human mobility data: A two-stage predictive framework with decomposition and multivariate analysis. Expert Syst Appl 238:121698. https:\/\/doi.org\/10.1016\/j.eswa.2023.121698","journal-title":"Expert Syst Appl"},{"issue":"17","key":"12348_CR66","doi-asserted-by":"publisher","first-page":"2453","DOI":"10.1080\/13504851.2024.2333995","volume":"32","author":"M Elorza","year":"2025","unstructured":"Elorza M, Castellano E, Segura S (2025) Prediction of customer demand for perishable products in retail inventory management, using the hybrid prophet-xgboost model during the post-covid-19 period. Appl Econ Lett 32(17):2453\u20132459. https:\/\/doi.org\/10.1080\/13504851.2024.2333995","journal-title":"Appl Econ Lett"},{"key":"12348_CR67","doi-asserted-by":"publisher","DOI":"10.1016\/j.clscn.2026.100319","volume":"19","author":"A Seyam","year":"2026","unstructured":"Seyam A, Mathew SS, Barachi ME et al (2026) A proactive food demand forecasting-inventory management approach under weather disruptions. Cleaner Logistics and Supply Chain 19:100319. https:\/\/doi.org\/10.1016\/j.clscn.2026.100319","journal-title":"Cleaner Logistics and Supply Chain"},{"key":"12348_CR68","doi-asserted-by":"publisher","first-page":"282","DOI":"10.1016\/j.cor.2016.11.005","volume":"81","author":"S Hamdan","year":"2017","unstructured":"Hamdan S, Cheaitou A (2017) Supplier selection and order allocation with green criteria: An mcdm and multi-objective optimization approach. Computers & Operations Research 81:282\u2013304. https:\/\/doi.org\/10.1016\/j.cor.2016.11.005","journal-title":"Computers & Operations Research"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-026-12348-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-026-12348-w","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-026-12348-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,5]],"date-time":"2026-09-05T04:46:44Z","timestamp":1788583604000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-026-12348-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8]]},"references-count":68,"journal-issue":{"issue":"15","published-print":{"date-parts":[[2026,8]]}},"alternative-id":["12348"],"URL":"https:\/\/doi.org\/10.1007\/s00521-026-12348-w","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,8]]},"assertion":[{"value":"21 January 2026","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 July 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 August 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.","order":1,"name":"Ethics","label":"Competing interests","group":{"name":"EthicsHeading","label":"Declarations"}}],"article-number":"641"}}