A fuzzy multi-objective optimization model for sustainable closed-loop supply chain network design in food industries
Citation
Nowadays, the intensification of a competitive environment in markets in conjunction with sustainability issues has forced organizations to concentrate on designing sustainable closed-loop supply chains. In this study, a sustainable closed-loop supply chain network is configured under uncertain conditions based on fuzzy theory. The proposed network is a multi-product multi-period problem which is formulated by a bi-objective mixed-integer linear programming model with fuzzy demand and return rate. The objectives are to maximize the supply chain profit and customer satisfaction at the same time. Moreover, the carbon footprint is included in the first objective function in terms of cost (tax) to affect the total profit and treat the environmental aspect. Fuzzy linear programming and Lp-metric method are then applied to deal with the uncertainty and bi-objectiveness of the model, respectively. In order to validate the methodology, a case study problem in the dairy industry is investigated where the proposed Lp-metric is also compared to goal attainment method. The obtained results demonstrate the superiority of Lp-metric against goal attainment method as well as the applicability and efficiency of the proposed methodology to treat a real case study problem. Furthermore, from the management perspective, outsourcing the production during high-demand periods is highly recommended as an efficient solution. © 2021, The Author(s), under exclusive licence to Springer Nature B.V.Abstract
Nowadays, the intensifcation of a competitive environment in markets in conjunction
with sustainability issues has forced organizations to concentrate on designing sustainable
closed-loop supply chains. In this study, a sustainable closed-loop supply chain network is
confgured under uncertain conditions based on fuzzy theory. The proposed network is a
multi-product multi-period problem which is formulated by a bi-objective mixed-integer
linear programming model with fuzzy demand and return rate. The objectives are to max imize the supply chain proft and customer satisfaction at the same time. Moreover, the
carbon footprint is included in the frst objective function in terms of cost (tax) to afect
the total proft and treat the environmental aspect. Fuzzy linear programming and Lp metric method are then applied to deal with the uncertainty and bi-objectiveness of the
model, respectively. In order to validate the methodology, a case study problem in the dairy
industry is investigated where the proposed Lp-metric is also compared to goal attainment
method. The obtained results demonstrate the superiority of Lp-metric against goal attain ment method as well as the applicability and efciency of the proposed methodology to
treat a real case study problem. Furthermore, from the management perspective, outsourc ing the production during high-demand periods is highly recommended as an efcient
solution.