A robust leader-follower approach for closed loop supply chain network design considering returns quality levels

• Published in: Computers & industrial engineering 2019-10, Vol.136, p.293-304
• Main Authors: Hassanpour, Atefeh, Bagherinejad, Jafar, Bashiri, Mahdi
• Format: Article
• Language: English
• Subjects: Bi-level programming; Closed-loop supply chain design; Genetic algorithm; Government regulation; Particle swarm optimization; Robust optimization
• ISSN: 0360-8352; 1879-0550
• DOI: 10.1016/j.cie.2019.07.031

•Presenting a leader-follower framework for the CLSC design based on governmental regulations.•Considering incentive strategy for different returned product quality levels in CLSC design.•Assessing the effect of governmental policies on CLSC design to achieve the optimum decisions.•Investigating of demand uncertainty on the government regulations by the robust optimization. This paper aims to assess the effect of governmental policies on a closed loop supply chain network design to achieve the optimum decision level of the collection policies for the government. For this purpose, a robust closed loop supply chain network design model with an incentive strategy for different return quality levels with a bi-level programming approach is proposed. The government will act as a leader in the outer problem and maximize the total collected returned products with different quality levels. A predefined ratio of customer demand should be satisfied as a constraint for the outer problem. In the inner problem, a closed loop supply chain designer is considered as a follower and tries to maximize the supply chain net profit with respect to government regulations. A heuristic method based on enumeration and a solution methodology consisting of particle swarm optimization for the outer problem and a genetic algorithm for the inner problem are proposed. In addition, we investigate the impact of demand uncertainty on government regulations and the closed loop supply chain configuration by a robust optimization approach. Finally, numerical examples are generated to evaluate the performance of the proposed model. The results show the necessity of using bi-level programming and the superiority of the proposed solution methodology compared with the proposed enumeration method in large-size problems.