Resilient mixed open and closed-loop supply chain network design under operational and disruption risks considering competition: A case study

This study addresses the problem of resilient mixed open and closed-loop supply chain network design under operational and disruption risks as a fundamental domain in supply chain management. To deal with disruption risks, several resilience strategies (including multiple sourcing, facility fortification, adding extra production capacity, multi-channel distribution, and pricing) are applied. A model with the objective of maximizing the profit is proposed, which uses a two-stage stochastic programming approach. In order to cope with the problem's complexity, a constructive heuristic method and two metaheuristics, including an improved genetic algorithm (IGA) and an improved particle swarm optimization (IPSO) are developed. After tuning the parameters of metaheuristics via the Taguchi method, various numerical instances are utilized to test the validity and efficiency of the model and solution methods. Further, a real industrial case study is provided and analyzed. Results show that the constructive heuristic outperforms other solution methods and the performed analysis indicates that utilizing resilient strategies has a remarkable effect on reducing losses originating from risks and maintaining market share against competitors.

Automated summary

This study addresses the problem of resilient mixed open and closed-loop supply chain network design and proposes a model with the objective of maximizing profit. To mitigate disruption risks, several resilience strategies are applied, and a two-stage stochastic programming approach is used. Constructive heuristic and metaheuristic methods (improved genetic algorithm and improved particle swarm optimization) are developed to deal with the problem's complexity. The results show the effectiveness of the proposed methods, and the analysis demonstrates the remarkable impact of resilient strategies on reducing risks and maintaining market share.