{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T21:44:27Z","timestamp":1780523067636,"version":"3.54.1"},"reference-count":66,"publisher":"Springer Science and Business Media LLC","issue":"8","license":[{"start":{"date-parts":[[2022,8,4]],"date-time":"2022-08-04T00:00:00Z","timestamp":1659571200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,8,4]],"date-time":"2022-08-04T00:00:00Z","timestamp":1659571200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Ambient Intell Human Comput"],"published-print":{"date-parts":[[2023,8]]},"DOI":"10.1007\/s12652-022-04357-z","type":"journal-article","created":{"date-parts":[[2022,8,4]],"date-time":"2022-08-04T13:09:37Z","timestamp":1659618577000},"page":"10867-10882","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["Big data-driven optimization for sustainable reverse logistics network design"],"prefix":"10.1007","volume":"14","author":[{"given":"Mohammad Amin","family":"Khoei","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Seyed Sina","family":"Aria","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hadi","family":"Gholizadeh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mark","family":"Goh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Naoufel","family":"Cheikhrouhou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2022,8,4]]},"reference":[{"key":"4357_CR1","doi-asserted-by":"crossref","first-page":"391","DOI":"10.1016\/j.resconrec.2015.07.006","volume":"104","author":"B Ayvaz","year":"2015","unstructured":"Ayvaz B, Bolat B, Ayd\u0131n N (2015) Stochastic reverse logistics network design for waste of electrical and electronic equipment. Resour Conserv Recycl 104:391\u2013404","journal-title":"Resour Conserv Recycl"},{"issue":"1","key":"4357_CR2","doi-asserted-by":"crossref","first-page":"188","DOI":"10.1016\/j.ejor.2017.10.057","volume":"269","author":"A Acquaye","year":"2018","unstructured":"Acquaye A, Ibn-Mohammed T, Genovese A, Afrifa GA, Yamoah FA, Oppon E (2018) A quantitative model for environmentally sustainable supply chain performance measurement. Eur J Oper Res 269(1):188\u2013205","journal-title":"Eur J Oper Res"},{"key":"4357_CR3","doi-asserted-by":"crossref","first-page":"276","DOI":"10.1016\/j.jclepro.2017.03.164","volume":"156","author":"C Arampantizi","year":"2017","unstructured":"Arampantizi C, Minis L (2017) A new model for designing sustainable supply chain networks and its application to a global manufacturer. J Clean Prod 156:276\u2013292","journal-title":"J Clean Prod"},{"key":"4357_CR4","doi-asserted-by":"crossref","DOI":"10.1016\/j.resconrec.2019.104448","volume":"150","author":"S Agrawal","year":"2019","unstructured":"Agrawal S, Singh RK (2019) Analyzing disposition decisions for sustainable reverse logistics: Triple bottom line approach. Resour Conserv Recycl 150:104448","journal-title":"Resour Conserv Recycl"},{"key":"4357_CR5","doi-asserted-by":"crossref","first-page":"2524","DOI":"10.1016\/j.jclepro.2016.11.023","volume":"142","author":"ZN Ansari","year":"2017","unstructured":"Ansari ZN, Kant R (2017) A state-of-art literature review reflecting 15 years of focus on sustainable supply chain management. J Clean Prod 142:2524\u20132543","journal-title":"J Clean Prod"},{"key":"4357_CR6","volume":"153","author":"S Bag","year":"2020","unstructured":"Bag S, Wood LC, Xu L, Dhamija P, Kayikci Y (2020) Big data analytics as an operational excellence approach to enhance sustainable supply chain performance. Resour Conserv Recycl 153:104559","journal-title":"Resour Conserv Recycl"},{"key":"4357_CR7","doi-asserted-by":"crossref","DOI":"10.1016\/j.jclepro.2019.119348","volume":"249","author":"P Dutta","year":"2020","unstructured":"Dutta P, Mishra A, Khandelwal S, Katthawala I (2020) A multiobjective optimization model for sustainable reverse logistics in Indian e-commerce market. J Clean Prod 249:119348","journal-title":"J Clean Prod"},{"key":"4357_CR8","doi-asserted-by":"crossref","first-page":"288","DOI":"10.1016\/j.compchemeng.2018.01.013","volume":"111","author":"E Dehghani","year":"2018","unstructured":"Dehghani E, Jabalameli MS, Jabbarzadeh A, Pishvaee MS (2018) Resilient solar photovoltaic supply chain network design under business-as-usual and hazard uncertainties. Comput Chem Eng 111:288\u2013310","journal-title":"Comput Chem Eng"},{"issue":"5\u20138","key":"4357_CR9","doi-asserted-by":"crossref","first-page":"1507","DOI":"10.1007\/s00170-016-9459-6","volume":"90","author":"A Entezaminia","year":"2017","unstructured":"Entezaminia A, Heidari M, Rahmani D (2017) Robust aggregate production planning in a green supply chain under uncertainty considering reverse logistics: A case study. Int J Adv Manufact Technol 90(5\u20138):1507\u20131528","journal-title":"Int J Adv Manufact Technol"},{"key":"4357_CR10","doi-asserted-by":"crossref","first-page":"176","DOI":"10.1016\/j.tre.2017.02.004","volume":"101","author":"M Fattahi","year":"2017","unstructured":"Fattahi M, Govindan K, Keyvanshokooh E (2017) Responsive and resilient supply chain network design under operational and disruption risks with delivery lead-time sensitive customers. Transport Res Part e Logist Transport Rev 101:176\u2013200","journal-title":"Transport Res Part e Logist Transport Rev"},{"key":"4357_CR11","doi-asserted-by":"crossref","DOI":"10.1016\/j.aei.2021.101418","volume":"50","author":"AM Fathollahi-Fard","year":"2021","unstructured":"Fathollahi-Fard AM, Dulebenets MA, Hajiaghaei-Keshteli M, Tavakkoli-Moghaddam R, Safaeian M, Mirzahosseinian H (2021) Two hybrid meta-heuristic algorithms for a dual-channel closed-loop supply chain network design problem in the tire industry under uncertainty. Adv Eng Inform 50:101418","journal-title":"Adv Eng Inform"},{"key":"4357_CR12","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1016\/j.tre.2018.04.014","volume":"115","author":"A Ghavamifar","year":"2018","unstructured":"Ghavamifar A, Makui A, Taleizadeh AA (2018) Designing a resilient competitive supply chain network under disruption risks: A real-world application. Transport Res Part e Logist Transport Rev 115:87\u2013109","journal-title":"Transport Res Part e Logist Transport Rev"},{"issue":"8","key":"4357_CR13","doi-asserted-by":"crossref","first-page":"3967","DOI":"10.1007\/s00521-018-3847-9","volume":"32","author":"H Gholizadeh","year":"2020","unstructured":"Gholizadeh H, Tajdin A, Javadian N (2020a) A closed-loop supply chain robust optimization for disposable products. Neural Comput Appl 32(8):3967\u20133985","journal-title":"Neural Comput Appl"},{"key":"4357_CR14","doi-asserted-by":"crossref","first-page":"120640","DOI":"10.1016\/j.jclepro.2020.120640","volume":"258","author":"H Gholizadeh","year":"2020","unstructured":"Gholizadeh H, Fazlollahtabar H, Khalilzadeh M (2020) A robust fuzzy stochastic programming for sustainable procurement and logistics under hybrid uncertainty using big data. J Clean Product 258:120640","journal-title":"J Clean Product"},{"key":"4357_CR15","doi-asserted-by":"crossref","DOI":"10.1016\/j.cie.2020.106653","volume":"147","author":"H Gholizadeh","year":"2020","unstructured":"Gholizadeh H, Fazlollahtabar H (2020) Robust Optimization and modified genetic algorithm for a closed loop green supply chain under uncertainty: Case study in melting industry. Comput Ind Eng 147:106653","journal-title":"Comput Ind Eng"},{"key":"4357_CR16","doi-asserted-by":"crossref","DOI":"10.1016\/j.cie.2021.107324","volume":"157","author":"H Gholizadeh","year":"2021","unstructured":"Gholizadeh H, Jahani H, Abareshi A, Goh M (2021) Sustainable closed-loop supply chain for dairy industry with robust and heuristic optimization. Comput Ind Eng 157:107324","journal-title":"Comput Ind Eng"},{"key":"4357_CR17","doi-asserted-by":"crossref","DOI":"10.1016\/j.cie.2021.107828","volume":"163","author":"H Gholizadeh","year":"2022","unstructured":"Gholizadeh H, Goh M, Fazlollahtabar H, Mamashli Z (2022) Modelling uncertainty in sustainable-green integrated reverse logistics network using metaheuristics optimization. Comput Ind Eng 163:107828","journal-title":"Comput Ind Eng"},{"key":"4357_CR18","doi-asserted-by":"crossref","first-page":"343","DOI":"10.1016\/j.tre.2018.03.011","volume":"114","author":"K Govindan","year":"2018","unstructured":"Govindan K, Cheng TCE, Mishra N, Shukla N (2018) Big data analytics and application for logistics and supply chain management. Transport Res Part e Logist Transport Rev 114:343\u2013349","journal-title":"Transport Res Part e Logist Transport Rev"},{"key":"4357_CR19","doi-asserted-by":"crossref","first-page":"371","DOI":"10.1016\/j.jclepro.2016.03.126","volume":"142","author":"K Govindan","year":"2017","unstructured":"Govindan K, Soleimani H (2017) A review of reverse logistics and closed-loop supply chains: a journal of cleaner production focus. J Clean Prod 142:371\u2013384","journal-title":"J Clean Prod"},{"key":"4357_CR20","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.omega.2018.05.007","volume":"85","author":"K Govindan","year":"2019","unstructured":"Govindan K, Kadzi\u0144ski M, Ehling R, Miebs G (2019) Selection of a sustainable third-party reverse logistics provider based on the robustness analysis of an outranking graph kernel conducted with ELECTRE I and SMAA. Omega 85:1\u201315","journal-title":"Omega"},{"key":"4357_CR21","doi-asserted-by":"crossref","DOI":"10.1016\/j.tre.2021.102279","volume":"149","author":"K Govindan","year":"2021","unstructured":"Govindan K, Gholizadeh H (2021) Robust network design for sustainable-resilient reverse logistics network using big data: A case study of end-of-life vehicles. Transport Res Part e Logist Transport Rev 149:102279","journal-title":"Transport Res Part e Logist Transport Rev"},{"key":"4357_CR22","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1016\/j.tre.2015.12.009","volume":"87","author":"A Hasani","year":"2016","unstructured":"Hasani A, Khosrojerdi A (2016) Robust global supply chain network design under disruption and uncertainty considering resilience strategies: A parallel memetic algorithm for a real-life case study. Transport Res Part e Logist Transport Rev 87:20\u201352","journal-title":"Transport Res Part e Logist Transport Rev"},{"issue":"17","key":"4357_CR23","doi-asserted-by":"crossref","first-page":"5945","DOI":"10.1080\/00207543.2018.1461950","volume":"56","author":"A Jabbarzadeh","year":"2018","unstructured":"Jabbarzadeh A, Fahimnia B, Sabouhi F (2018) Resilient and sustainable supply chain design: Sustainability analysis under disruption risks. Int J Prod Res 56(17):5945\u20135968","journal-title":"Int J Prod Res"},{"key":"4357_CR24","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1016\/j.trb.2016.09.004","volume":"94","author":"A Jabbarzadeh","year":"2016","unstructured":"Jabbarzadeh A, Fahimnia B, Sheu JB, Moghadam HS (2016) Designing a supply chain resilient to major disruptions and supply\/demand interruptions. Transport Res Part b Methodol 94:121\u2013149","journal-title":"Transport Res Part b Methodol"},{"key":"4357_CR25","doi-asserted-by":"crossref","unstructured":"Keshavarz E, Toloo M (2019) Selecting third-party reverse logistics providers under uncertainty. In 6th International Conference on Control, Decision and Information Technologies (CoDIT) (pp. 1528\u20131532). IEEE","DOI":"10.1109\/CoDIT.2019.8820453"},{"key":"4357_CR26","doi-asserted-by":"crossref","first-page":"1282","DOI":"10.1016\/j.jclepro.2018.06.015","volume":"195","author":"Y Kazancoglu","year":"2018","unstructured":"Kazancoglu Y, Kazancoglu I, Sagnak M (2018) A new holistic conceptual framework for green supply chain management performance assessment based on circular economy. J Clean Prod 195:1282\u20131299","journal-title":"J Clean Prod"},{"key":"4357_CR27","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1016\/j.cor.2017.05.008","volume":"98","author":"H Kaur","year":"2018","unstructured":"Kaur H, Singh SP (2018) Heuristic modeling for sustainable procurement and logistics in a supply chain using big data. Comput Oper Res 98:301\u2013321","journal-title":"Comput Oper Res"},{"issue":"1","key":"4357_CR28","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1007\/s10479-016-2374-2","volume":"283","author":"H Kaur","year":"2019","unstructured":"Kaur H, Singh SP (2019) Sustainable procurement and logistics for disaster resilient supply chain. Ann Oper Res 283(1):309\u2013354","journal-title":"Ann Oper Res"},{"issue":"2","key":"4357_CR29","doi-asserted-by":"crossref","first-page":"882","DOI":"10.1016\/j.ijpe.2011.10.028","volume":"135","author":"W Klibi","year":"2012","unstructured":"Klibi W, Martel A (2012) Modeling approaches for the design of resilient supply networks under disruptions. Int J Prod Econ 135(2):882\u2013898","journal-title":"Int J Prod Econ"},{"key":"4357_CR30","doi-asserted-by":"crossref","DOI":"10.1007\/978-0-387-87817-1","volume-title":"Modeling with Stochastic Programming","author":"AJ King","year":"2012","unstructured":"King AJ, Wallace SW (2012) Modeling with Stochastic Programming. Springer Science & Business Media, New York"},{"key":"4357_CR31","doi-asserted-by":"crossref","first-page":"479","DOI":"10.1137\/S1052623499363220","volume":"12","author":"AJ Kleywegt","year":"2002","unstructured":"Kleywegt AJ, Shapiro A, Homem-De-Mello T (2002) The sample average approximation method for stochastic discrete optimization. SIAM J Optim 12:479\u2013502","journal-title":"SIAM J Optim"},{"key":"4357_CR32","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1016\/j.aei.2017.01.003","volume":"32","author":"S Lan","year":"2017","unstructured":"Lan S, Yang C, Huang GQ (2017) Data analysis for metropolitan economic and logistics development. Adv Eng Inform 32:66\u201376","journal-title":"Adv Eng Inform"},{"issue":"2","key":"4357_CR33","doi-asserted-by":"crossref","first-page":"1216","DOI":"10.1007\/s40815-021-01209-4","volume":"24","author":"R Lotfi","year":"2022","unstructured":"Lotfi R, Kargar B, Rajabzadeh M, Hesabi F, \u00d6zceylan E (2022a) Hybrid fuzzy and data-driven robust optimization for resilience and sustainable health care supply chain with vendor-managed inventory approach. Int J Fuzzy Syst 24(2):1216\u20131231","journal-title":"Int J Fuzzy Syst"},{"key":"4357_CR34","doi-asserted-by":"crossref","unstructured":"Lotfi R, Kargar B, Gharehbaghi A, Afshar M, Rajabi MS, Mardani N (2022b) A data-driven robust optimization for multi-objective renewable energy location by considering risk. Environment, Development and Sustainability, 1\u201322","DOI":"10.1007\/s10668-022-02448-7"},{"key":"4357_CR35","doi-asserted-by":"crossref","unstructured":"Li Y, Yang J, Wen J (2021) Entropy-based redundancy analysis and information screening. Digital Commun Netw","DOI":"10.1016\/j.dcan.2021.12.001"},{"issue":"1","key":"4357_CR36","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1007\/s40171-019-00225-6","volume":"20","author":"J Mari\u0107","year":"2019","unstructured":"Mari\u0107 J, Opazo-Bas\u00e1ez M (2019) Green servitization for flexible and sustainable supply chain operations: A review of reverse logistics services in manufacturing. Glob J Flex Syst Manag 20(1):65\u201380","journal-title":"Glob J Flex Syst Manag"},{"key":"4357_CR37","doi-asserted-by":"crossref","unstructured":"Mishra S, Singh SP (2020a) A stochastic disaster-resilient and sustainable reverse logistics model in big data environment. Ann Oper Res 1\u201332","DOI":"10.1007\/s10479-020-03573-0"},{"issue":"4","key":"4357_CR38","doi-asserted-by":"crossref","first-page":"709","DOI":"10.1007\/s40092-018-0287-1","volume":"15","author":"ST Moghaddam","year":"2019","unstructured":"Moghaddam ST, Javadi M, Molana SMH (2019) A reverse logistics chain mathematical model for a sustainable production system of perishable goods based on demand optimization. J Indust Eng Int 15(4):709\u2013721","journal-title":"J Indust Eng Int"},{"issue":"10","key":"4357_CR39","doi-asserted-by":"crossref","first-page":"1038","DOI":"10.3390\/su8101038","volume":"8","author":"SI Mari","year":"2016","unstructured":"Mari SI, Lee YH, Memon MS (2016) Sustainable and resilient garment supply chain network design with fuzzy multi-objectives under uncertainty. Sustainability 8(10):1038","journal-title":"Sustainability"},{"key":"4357_CR40","doi-asserted-by":"crossref","first-page":"297","DOI":"10.1016\/j.cie.2018.09.052","volume":"127","author":"A Mohammed","year":"2019","unstructured":"Mohammed A, Harris I, Soroka A, Nujoom R (2019) A hybrid MCDM-fuzzy multi-objective programming approach for a G-resilient supply chain network design. Comput Ind Eng 127:297\u2013312","journal-title":"Comput Ind Eng"},{"key":"4357_CR41","doi-asserted-by":"crossref","first-page":"102983","DOI":"10.1016\/j.ijdrr.2022.102983","volume":"75","author":"J Moosavi","year":"2022","unstructured":"Moosavi J, Fathollahi-Fard AM, Dulebenets MA (2022) Supply chain disruption during the COVID-19 pandemic: Recognizing potential disruption management strategies. Int J Disaster Risk Reduct 75:102983","journal-title":"Int J Disaster Risk Reduct"},{"issue":"4","key":"4357_CR42","first-page":"360","volume":"6","author":"YZ Mehrjerdi","year":"2019","unstructured":"Mehrjerdi YZ, Lotfi R (2019) Development of a mathematical model for sustainable closed-loop supply chain with efficiency and resilience systematic framework. Int J Supply Oper Manag 6(4):360\u2013388","journal-title":"Int J Supply Oper Manag"},{"key":"4357_CR43","doi-asserted-by":"crossref","DOI":"10.1016\/j.scitotenv.2019.135549","volume":"707","author":"S Mishra","year":"2020","unstructured":"Mishra S, Singh SP (2020b) Distribution network model using big data in an international environment. Sci Total Environ 707:135549","journal-title":"Sci Total Environ"},{"key":"4357_CR44","doi-asserted-by":"crossref","first-page":"107808","DOI":"10.1016\/j.cie.2021.107808","volume":"163","author":"M Pourmehdi","year":"2022","unstructured":"Pourmehdi M, Paydar MM, Ghadimi P, Azadnia AH (2022) Analysis and evaluation of challenges in the integration of Industry 40 and sustainable steel reverse logistics network. Computers Indust Eng 163:107808","journal-title":"Computers Indust Eng"},{"key":"4357_CR45","doi-asserted-by":"crossref","first-page":"1567","DOI":"10.1016\/j.jclepro.2017.10.240","volume":"172","author":"M Rahimi","year":"2018","unstructured":"Rahimi M, Ghezavati V (2018) Sustainable multi-period reverse logistics network design and planning under uncertainty utilizing conditional value at risk (CVaR) for recycling construction and demolition waste. J Clean Prod 172:1567\u20131581","journal-title":"J Clean Prod"},{"key":"4357_CR46","doi-asserted-by":"crossref","first-page":"74","DOI":"10.1016\/j.spc.2018.05.005","volume":"15","author":"R Rajesh","year":"2018","unstructured":"Rajesh R (2018) On sustainability, resilience, and the sustainable-resilient supply networks. Sustain Prod Consump 15:74\u201388","journal-title":"Sustain Prod Consump"},{"issue":"3","key":"4357_CR47","doi-asserted-by":"crossref","first-page":"1017","DOI":"10.1016\/j.ejor.2016.11.041","volume":"259","author":"S Rezapour","year":"2017","unstructured":"Rezapour S, Farahani RZ, Pourakbar M (2017) Resilient supply chain network design under competition: A case study. Eur J Oper Res 259(3):1017\u20131035","journal-title":"Eur J Oper Res"},{"key":"4357_CR48","doi-asserted-by":"crossref","unstructured":"Shapiro A (2003) Monte Carlo sampling approach to stochastic programming. ESAIM: Proceedings, 2003. EDP Sciences, 65\u201373","DOI":"10.1051\/proc:2003003"},{"key":"4357_CR49","doi-asserted-by":"crossref","first-page":"409","DOI":"10.1016\/j.ejor.2008.11.040","volume":"199","author":"P Sch\u00fctz","year":"2009","unstructured":"Sch\u00fctz P, Tomasgard A, Ahmed S (2009) Supply chain design under uncertainty using sample average approximation and dual decomposition. Eur J Oper Res 199:409\u2013419","journal-title":"Eur J Oper Res"},{"key":"4357_CR50","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1016\/j.ijpe.2018.05.030","volume":"217","author":"PC Sauer","year":"2018","unstructured":"Sauer PC, Seuring S (2018) Extending the reach of multi-tier sustainable supply chain management \u2013 Insights from mineral supply chains. Int J Prod Econ 217:31\u201343","journal-title":"Int J Prod Econ"},{"issue":"4","key":"4357_CR51","doi-asserted-by":"crossref","first-page":"991","DOI":"10.1108\/IJESM-03-2018-0005","volume":"13","author":"MJ Sepehr","year":"2019","unstructured":"Sepehr MJ, Haeri A, Ghousi R (2019) A cross-country evaluation of energy efficiency from the sustainable development perspective. Int J Energy Sect Manage 13(4):991\u20131019","journal-title":"Int J Energy Sect Manage"},{"key":"4357_CR52","doi-asserted-by":"crossref","unstructured":"Seydanlou P, Jolai F, Tavakkoli-Moghaddam R, Fathollahi-Fard AM (2022) A multi-objective optimization framework for a sustainable closed-loop supply chain network in the olive industry: Hybrid meta-heuristic algorithms. Expert Syst Appl 117566","DOI":"10.1016\/j.eswa.2022.117566"},{"issue":"7","key":"4357_CR53","doi-asserted-by":"crossref","first-page":"642","DOI":"10.1080\/0951192X.2019.1599443","volume":"32","author":"S Singh","year":"2019","unstructured":"Singh S, Ghosh S, Jayaram J, Tiwari MK (2019) Enhancing supply chain resilience using ontology-based decision support system. Int J Comput Integr Manuf 32(7):642\u2013657","journal-title":"Int J Comput Integr Manuf"},{"key":"4357_CR54","doi-asserted-by":"crossref","unstructured":"Soleimani H, Chhetri P, Fathollahi-Fard AM, Mirzapour Al-e-Hashem SMJ, Shahparvari S (2022) Sustainable closed-loop supply chain with energy efficiency: Lagrangian relaxation, reformulations and heuristics. Ann Oper Res 1\u201326","DOI":"10.1007\/s10479-022-04661-z"},{"key":"4357_CR55","doi-asserted-by":"crossref","DOI":"10.1016\/j.jclepro.2019.118818","volume":"245","author":"J Trochu","year":"2020","unstructured":"Trochu J, Chaabane A, Ouhimmou M (2020) A carbon-constrained stochastic model for eco-efficient reverse logistics network design under environmental regulations in the CRD industry. J Clean Prod 245:118818","journal-title":"J Clean Prod"},{"key":"4357_CR56","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1023\/A:1021814225969","volume":"24","author":"B Verweij","year":"2003","unstructured":"Verweij B, Ahmed S, Kleywegt AJ, Nemhauser GL, Shapiro A (2003) The sample average approximation method applied to stochastic routing problems: A computational study. Comput Optim Appl 24:289\u2013333","journal-title":"Comput Optim Appl"},{"key":"4357_CR57","doi-asserted-by":"crossref","first-page":"98","DOI":"10.1016\/j.ijpe.2016.03.014","volume":"176","author":"G Wang","year":"2016","unstructured":"Wang G, Gunasekaran A, Ngai EW, Papadopoulos T (2016) Big data analytics in logistics and supply chain management: Certain investigations for research and applications. Int J Prod Econ 176:98\u2013110","journal-title":"Int J Prod Econ"},{"issue":"4","key":"4357_CR58","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1109\/MNET.011.1900374","volume":"34","author":"J Yang","year":"2020","unstructured":"Yang J, Wen J, Jiang B, Wang H (2020) Blockchain-based sharing and tamper-proof framework of big data networking. IEEE Network 34(4):62\u201367","journal-title":"IEEE Network"},{"key":"4357_CR59","doi-asserted-by":"crossref","first-page":"285","DOI":"10.1016\/j.jclepro.2018.07.019","volume":"198","author":"H Yu","year":"2018","unstructured":"Yu H, Solvang WD (2018) Incorporating flexible capacity in the planning of a multi-product multi-echelon sustainable reverse logistics network under uncertainty. J Clean Prod 198:285\u2013303","journal-title":"J Clean Prod"},{"key":"4357_CR60","volume":"277","author":"H Yu","year":"2020","unstructured":"Yu H, Sun X, Solvang WD, Laporte G, Lee CKM (2020) A stochastic network design problem for hazardous waste management. J Clean Prod 277:123566","journal-title":"J Clean Prod"},{"key":"4357_CR61","doi-asserted-by":"crossref","first-page":"121702","DOI":"10.1016\/j.jclepro.2020.121702","volume":"266","author":"H Yu","year":"2020","unstructured":"Yu H, Solvang WD (2020) A fuzzy-stochastic multi-objective model for sustainable planning of a closed-loop supply chain considering mixed uncertainty and network flexibility. J Clean Prod 266:121702","journal-title":"J Clean Prod"},{"key":"4357_CR62","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1016\/j.tre.2017.04.009","volume":"103","author":"B Zahiri","year":"2017","unstructured":"Zahiri B, Zhuang J, Mohammadi M (2017) Toward an integrated sustainable-resilient supply chain: A pharmaceutical case study. Transport Res Part e: Logist Transport Rev 103:109\u2013142","journal-title":"Transport Res Part e: Logist Transport Rev"},{"key":"4357_CR63","doi-asserted-by":"crossref","DOI":"10.1016\/j.jclepro.2019.118461","volume":"242","author":"N Zarbakhshnia","year":"2020","unstructured":"Zarbakhshnia N, Wu Y, Govindan K, Soleimani H (2020) A novel hybrid multiple attribute decision-making approach for outsourcing sustainable reverse logistics. J Clean Prod 242:118461","journal-title":"J Clean Prod"},{"key":"4357_CR64","doi-asserted-by":"crossref","first-page":"306","DOI":"10.1016\/j.aei.2018.07.007","volume":"38","author":"L Zhen","year":"2018","unstructured":"Zhen L, Wu Y, Wang S, Hu Y, Yi W (2018) Capacitated closed-loop supply chain network design under uncertainty. Adv Eng Inform 38:306\u2013315","journal-title":"Adv Eng Inform"},{"key":"4357_CR65","volume":"49","author":"S Zhu","year":"2021","unstructured":"Zhu S, Gao J, He X, Zhang S, Jin Y, Tan Z (2021) Green logistics oriented tug scheduling for inland waterway logistics. Adv Eng Inform 49:101323","journal-title":"Adv Eng Inform"},{"key":"4357_CR66","doi-asserted-by":"crossref","DOI":"10.1016\/j.aei.2021.101322","volume":"49","author":"Z Zhuang","year":"2021","unstructured":"Zhuang Z, Fu S, Lan S, Yu H, Yang C, Huang GQ (2021) Research on economic benefits of multi-city logistics development based on data-driven analysis. Adv Eng Inform 49:101322","journal-title":"Adv Eng Inform"}],"container-title":["Journal of Ambient Intelligence and Humanized Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12652-022-04357-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s12652-022-04357-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12652-022-04357-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,6,21]],"date-time":"2023-06-21T14:08:52Z","timestamp":1687356532000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s12652-022-04357-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,8,4]]},"references-count":66,"journal-issue":{"issue":"8","published-print":{"date-parts":[[2023,8]]}},"alternative-id":["4357"],"URL":"https:\/\/doi.org\/10.1007\/s12652-022-04357-z","relation":{},"ISSN":["1868-5137","1868-5145"],"issn-type":[{"value":"1868-5137","type":"print"},{"value":"1868-5145","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,8,4]]},"assertion":[{"value":"17 December 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 July 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"4 August 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}