A DISTRIBUTED EVOLUTIONARY ALGORITHM FOR SOLVING THE GREEN SUPPLY CHAIN NETWORK DESIGN PROBLEM

This paper proposes an extended Multi-objective Mathematical Model for the Green Supply Chain (GSC) network design problem, taking green procurement, production, distribution, and transportation into consideration. The triple-bottom-line in GSC is defined and assigned indicators to evaluate potential partners for further operations. In addition, an efficient and flexible Self-Adaptive Distributed Evolutionary Algorithm (SADEA) is developed to undertake strategic, tactical, and operational decision making. The algorithm employs a hybrid tree coding structure with a self-adaptive operator selection pool and is paralleled and implemented in Spark to further improve its efficiency. Our results demonstrate that the algorithm can solve the GSC network design problem efficiently and provide high quality solutions compared to other algorithms for the multi-objective optimization. The study results provide an important reference to guide future research.