TY - JOUR
T1 - A comprehensive framework for sustainable closed-loop supply chain network design
AU - Tavana, Madjid
AU - Kian, Hadi
AU - Nasr, Arash Khalili
AU - Govindan, Kannan
AU - Mina, Hassan
N1 - Funding Information:
Dr. Madjid Tavana is grateful for the partial support he received from the Czech Science Foundation ( GAČR19-13946S ) for this research.
Publisher Copyright:
© 2021 The Authors
PY - 2022/1/15
Y1 - 2022/1/15
N2 - 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.
AB - 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.
KW - Fuzzy goal programming
KW - Location-inventory-routing
KW - Network design
KW - Pickup and delivery
KW - Sustainable CLSC
U2 - 10.1016/j.jclepro.2021.129777
DO - 10.1016/j.jclepro.2021.129777
M3 - Journal article
AN - SCOPUS:85121227037
SN - 0959-6526
VL - 332
JO - Journal of Cleaner Production
JF - Journal of Cleaner Production
M1 - 129777
ER -