A comprehensive framework for sustainable closed-loop supply chain network design

• Published in: Journal of cleaner production Vol. 332; p. 129777
• Main Authors: Tavana, Madjid, Kian, Hadi, Nasr, Arash Khalili, Govindan, Kannan, Mina, Hassan
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 15.01.2022
• Subjects: Fuzzy goal programming; Location-inventory-routing; Network design; Pickup and delivery; Sustainable CLSC; Sustainable CLSC; Fuzzy goal programming; Network design; Pickup and delivery; Location-inventory-routing
• ISSN: 0959-6526; 1879-1786
• DOI: 10.1016/j.jclepro.2021.129777

Many companies face challenges in reducing their supply chain costs while increasing sustainability and customer service levels. A comprehensive framework for a sustainable closed-loop supply chain (CLSC) network is a practical solution to these challenges. Hence, for the first time, this study considers an integrated multi-objective mixed-integer linear programming (MOMILP) model to design sustainable CLSC networks with cross-docking, location-inventory-routing, time window, supplier selection, order allocation, transportation modes with simultaneous pickup, and delivery under uncertainty. An intelligent simulation algorithm is proposed to produce CLSC network data with probabilistic distribution functions and feasible solution space. In addition, a fuzzy goal programming approach is proposed to solve the MOMILP model under uncertainty. Eight small and medium-size test problems are used to evaluate the performance of the proposed model with the simulated data in GAMS software. The results obtained from test problems and sensitivity analysis show the efficacy of the proposed model. [Display omitted] •We propose a comprehensive sustainable closed-loop supply chain (CLSC) network.•The CLSC contains cross-docking, location-inventory-routing, and pickup and delivery.•A multi-objective mixed-integer linear model is developed to optimize the CLSC network.•An intelligent simulation generates CLSC data using probabilistic distribution functions.•Fuzzy goal programming solves the proposed multi-objective model under uncertainty.