Bi-objective green supply chain network design under disruption risk through an extended NSGA-II algorithm

Abstract

Green supply chain network design plays an important role in reducing environmental pollution and resource consumption. Furthermore, emergency events may cause disruptions and seriously reduce the performance of entire supply chain. This paper considers a three-echelon supply chain network consisting of multi-manufacturers, retailers with disruption risks and capacity constraints, and consumers with green preference. Different from traditional supply chain network design, this paper considers respectively two objectives from the manufacturers and consumers with green preference in selecting appropriate retailers under disruption risks. Moreover, we propose an extended elitist non-dominated sorting genetic algorithm (NSGA-II) to solve the bi-objective optimization model. The extended algorithm is considered to combine original NSGA-II algorithm with the migration operation of the biogeography-based optimization (BBO) algorithm, thus leading to enrich the diversity of the population and improve the ability of global searching. Compared with the traditional NSGA-II algorithm, the extended NSGA-II algorithm can obtain more Pareto solutions with higher efficiency. Furthermore, the result shows a trade-off relationship between the manufacturer cost and consumer cost. Therefore, it is necessary to separate the two objectives of manufacturers and consumers in green supply chain network design.