{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T06:47:35Z","timestamp":1777704455467,"version":"3.51.4"},"reference-count":50,"publisher":"SAGE Publications","issue":"5","license":[{"start":{"date-parts":[[2020,10,10]],"date-time":"2020-10-10T00:00:00Z","timestamp":1602288000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"published-print":{"date-parts":[[2020,11,19]]},"abstract":"<jats:p>The problem of the optimal three-level location allocation of transfer center, processing factory and distribution center for supply chain network under uncertain transportation cost and customer demand are studied. We establish a two-stage fuzzy 0-1 mixed integer optimization model, by considering the uncertainty of the supply chain. Given the complexity of the model, this paper proposes a modified hybrid second order particle swarm optimization algorithm (MHSO-PSO) to solve the resulting model, yielding the optimal location and maximal expected return of supply chain simultaneously. A case study of clothing supply chain in Shanghai of China is then presented to investigate the specific influence of uncertainties on the transfer center, clothing factory and distribution center three-level location. Moreover, we compare the MHSO-PSO with hybrid particle swarm optimization algorithm and hybrid genetic algorithm, to validate the proposed algorithm based on the computational time and the convergence rate.<\/jats:p>","DOI":"10.3233\/jifs-191453","type":"journal-article","created":{"date-parts":[[2020,10,13]],"date-time":"2020-10-13T12:50:33Z","timestamp":1602593433000},"page":"6741-6756","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":2,"title":["Two-stage fuzzy mixed integer optimization model for three-level location allocation problems under uncertain environment"],"prefix":"10.1177","volume":"39","author":[{"given":"Zhimin","family":"Liu","sequence":"first","affiliation":[{"name":"School of Mathematics Science, Liaocheng University, Liaocheng, China"},{"name":"Business School, University of Shanghai for Science and Technology, Shanghai, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shaojian","family":"Qu","sequence":"additional","affiliation":[{"name":"Nanjing University of Information Science and Technology, Nanjing, China"},{"name":"National University of Singapore, Singapore"},{"name":"Business School, University of Shanghai for Science and Technology, Shanghai, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhong","family":"Wu","sequence":"additional","affiliation":[{"name":"Business School, University of Shanghai for Science and Technology, Shanghai, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ying","family":"Ji","sequence":"additional","affiliation":[{"name":"Business School, University of Shanghai for Science and Technology, Shanghai, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2020,10,10]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1287\/opre.11.3.331"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.1287\/mnsc.22.1.57"},{"key":"e_1_3_2_4_2","doi-asserted-by":"publisher","DOI":"10.1016\/0377-2217(87)90218-9"},{"key":"e_1_3_2_5_2","first-page":"4237","article-title":"Shelter location-allocation model for flood evacuation planning","volume":"6","author":"Chen A.","year":"2009","unstructured":"ChenA., Shelter location-allocation model for flood evacuation planning, Journal of the Eastern Asia Society for Transportation Studies 6 (2009), 4237\u20134252.","journal-title":"Journal of the Eastern Asia Society for Transportation Studies"},{"key":"e_1_3_2_6_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.compenvurbsys.2016.07.001"},{"key":"e_1_3_2_7_2","doi-asserted-by":"crossref","unstructured":"QuS.J. ZhouY.Y. ZhangY.L. WahabM. ZhangG. and YeY.Y. Optimal strategy for a green supply chain considering shipping policy and default risk Computers and Industrial Engineering (2019) 172\u2013186.","DOI":"10.1016\/j.cie.2019.03.042"},{"key":"e_1_3_2_8_2","doi-asserted-by":"crossref","unstructured":"ValidiS. BhattacharyaA. and ByrneP.J. Sustainable distribution system design: a two-phase DoE-guided meta-heuristic solution approach for a three-echelon bi-objective AHP-integrated location-routing model Annals of Operations Research (2018) 1\u201332.","DOI":"10.1007\/s10479-018-2887-y"},{"key":"e_1_3_2_9_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijpe.2019.01.011"},{"key":"e_1_3_2_10_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.tre.2018.05.003"},{"key":"e_1_3_2_11_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejor.2018.02.022"},{"key":"e_1_3_2_12_2","doi-asserted-by":"publisher","DOI":"10.3233\/JIFS-181997"},{"key":"e_1_3_2_13_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10479-017-2741-7"},{"key":"e_1_3_2_14_2","doi-asserted-by":"publisher","DOI":"10.35833\/MPCE.2019.000131"},{"key":"e_1_3_2_15_2","doi-asserted-by":"publisher","DOI":"10.1111\/itor.12698"},{"key":"e_1_3_2_16_2","doi-asserted-by":"publisher","unstructured":"LiuZ.M. QuS.J. HassanR. WuZ. QuD.Q. and DuJ.H. Twostage mean-risk stochastic mixed integer optimization model for location-allocation problems under uncertain environment Journal of Industrial and Management Optimization (2020) doi:10.3934\/jimo.2020094","DOI":"10.3934\/jimo.2020094"},{"key":"e_1_3_2_17_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0019-9958(65)90241-X"},{"key":"e_1_3_2_18_2","doi-asserted-by":"publisher","DOI":"10.1016\/0165-0114(92)90018-Y"},{"key":"e_1_3_2_19_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejor.2006.11.029"},{"key":"e_1_3_2_20_2","first-page":"14","article-title":"A fuzzy coherent hierarchical location-allocation model for congested systems","volume":"13","author":"Shavandi H.","year":"2006","unstructured":"ShavandiH., EshghiK., MahloujiH. and KhanM.S., A fuzzy coherent hierarchical location-allocation model for congested systems, Scientia Iranica 13 (2006), 14\u201324.","journal-title":"Scientia Iranica"},{"key":"e_1_3_2_21_2","doi-asserted-by":"crossref","unstructured":"ShenS.Y. LiuY.K. and BaiX.J. Modeling location-allocation problem by two-stage fuzzy programming International Conference on Machine Learning and Cybernetics (2009) 722\u2013727.","DOI":"10.1109\/ICMLC.2009.5212385"},{"key":"e_1_3_2_22_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10845-009-0297-3"},{"key":"e_1_3_2_23_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.apm.2012.10.038"},{"key":"e_1_3_2_24_2","doi-asserted-by":"publisher","DOI":"10.1142\/S0219622014500400"},{"key":"e_1_3_2_25_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1155\/2014\/472623","article-title":"Minimum risk facility location-allocation problem with type-2 fuzzy variables","volume":"2014","author":"Bai X.J.","year":"2014","unstructured":"BaiX.J. and LiuY., Minimum risk facility location-allocation problem with type-2 fuzzy variables, The Scientific World Journal 2014 (2014), 1\u20139.","journal-title":"The Scientific World Journal"},{"key":"e_1_3_2_26_2","doi-asserted-by":"crossref","unstructured":"GongY. PengY. and HuangD. A fuzzy chance constraint programming approach for location-allocation problem under uncertainty in a closed-loop supply chain International Joint Conference on Computational Sciences and Optimization IEEE Computer Society 2009.","DOI":"10.1109\/CSO.2009.151"},{"key":"e_1_3_2_27_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cie.2006.06.019"},{"key":"e_1_3_2_28_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00170-010-2896-8"},{"key":"e_1_3_2_29_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0165-0114(98)00459-X"},{"key":"e_1_3_2_30_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijleo.2016.06.032"},{"key":"e_1_3_2_31_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cie.2018.03.041"},{"key":"e_1_3_2_32_2","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2009.2022542"},{"key":"e_1_3_2_33_2","doi-asserted-by":"publisher","DOI":"10.3846\/16484142.2014.983966"},{"key":"e_1_3_2_34_2","doi-asserted-by":"publisher","DOI":"10.1109\/TSMCB.2009.2035630"},{"key":"e_1_3_2_35_2","doi-asserted-by":"crossref","unstructured":"NoyanN. Risk-averse stochastic modeling and optimization In INFORMS TutORials in Operations Research (2008) 221\u2013254.","DOI":"10.1287\/educ.2018.0183"},{"key":"e_1_3_2_36_2","doi-asserted-by":"publisher","DOI":"10.1023\/A:1013827731218"},{"key":"e_1_3_2_37_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0927-0507(03)10003-5"},{"key":"e_1_3_2_38_2","doi-asserted-by":"publisher","DOI":"10.1016\/0098-1354(95)87027-X"},{"key":"e_1_3_2_39_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejor.2002.11.006"},{"key":"e_1_3_2_40_2","doi-asserted-by":"publisher","DOI":"10.1057\/jors.1979.78"},{"key":"e_1_3_2_41_2","unstructured":"StidsenT.R. AndersenK.A. and DammannB. A branch and bound algorithm for a class of bi-objective mixed integer programs Informs 2014."},{"key":"e_1_3_2_42_2","doi-asserted-by":"publisher","DOI":"10.1007\/s001860100120"},{"key":"e_1_3_2_43_2","unstructured":"MedskerL.R. Hybrid intelligent systems kluwer academic publishers Boston 1995."},{"key":"e_1_3_2_44_2","doi-asserted-by":"crossref","unstructured":"LiuB. Theory and practice of uncertain programming Heidelberg: Physica-Verlag 2002.","DOI":"10.1007\/978-3-7908-1781-2"},{"key":"e_1_3_2_45_2","unstructured":"LiuB. Uncertainty theory-a branch of mathematics for modeling human uncertainty Springer 2010."},{"key":"e_1_3_2_46_2","unstructured":"YagerR.R. and KaeprzykJ. The ordered weighted averaging operator: theory and applications Kluwer Aeademie Publishers Boston MA 1997."},{"key":"e_1_3_2_47_2","doi-asserted-by":"crossref","unstructured":"MaQ. LeiX. and ZhangQ. Mobile robot path planning with complex constraints based on the second-order oscillating particle swarm optimization algorithm World Congress on Computer Science and Information Engineering (2009) 244\u2013248.","DOI":"10.1109\/CSIE.2009.124"},{"key":"e_1_3_2_48_2","doi-asserted-by":"publisher","DOI":"10.1109\/4235.985692"},{"key":"e_1_3_2_49_2","first-page":"4104","article-title":"A discrete binary version of the particle swarm algorithm","volume":"5","author":"Kennedy J.","year":"1997","unstructured":"KennedyJ. and EberhartR.C., A discrete binary version of the particle swarm algorithm, IEEE International Conference on Systems, Man, and Cybernetics 5 (1997), 4104\u20134108.","journal-title":"IEEE International Conference on Systems, Man, and Cybernetics"},{"key":"e_1_3_2_50_2","unstructured":"GoldbergD.E. Genetic algorithms in Search optimization and machine learning Reading MA: Addison-Wesley 1989."},{"key":"e_1_3_2_51_2","doi-asserted-by":"publisher","DOI":"10.1109\/TSMCB.2008.2004501"}],"container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.3233\/JIFS-191453","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.3233\/JIFS-191453","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.3233\/JIFS-191453","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T09:41:15Z","timestamp":1777455675000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.3233\/JIFS-191453"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,10,10]]},"references-count":50,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2020,11,19]]}},"alternative-id":["10.3233\/JIFS-191453"],"URL":"https:\/\/doi.org\/10.3233\/jifs-191453","relation":{},"ISSN":["1064-1246","1875-8967"],"issn-type":[{"value":"1064-1246","type":"print"},{"value":"1875-8967","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,10,10]]}}}