Multi-echelon sustainable reverse logistics network design with incentive mechanism for eco-packages

• Published in: Journal of cleaner production 2023-12, Vol.430, p.139500, Article 139500
• Main Authors: Zhou, Ji, Yang, Senyan, Feng, Hui, An, Zexu
• Format: Article
• Language: English
• Subjects: Eco-packages; Green reverse logistics; Heuristics algorithm; Incentive mechanism; Location-routing problem; Multi-objective optimization
• ISSN: 0959-6526; 1879-1786
• DOI: 10.1016/j.jclepro.2023.139500

With the pollution caused by express packaging waste, eco-packages are being commonly used to promote a green supply chain. However, extant research has yet to address the efficacious reverse logistics network design problem while considering both economic and environmental consumption in the recycling process. In this study, a multi-echelon reverse logistics network is designed to collect eco-packages from customers, instead of door-to-door recycling by couriers. This study aims to solve the capacity location-routing problem in a reverse logistics network integrated with the incentive mechanism for customers, which is regarded as NP-hard. To avoid the combinatorial explosion, a multi-objective hybrid genetic algorithm-tabu search (MOHGATS) is developed to reduce search space and improve search speed by changing search strategies. Computational experiments are conducted to verify the proposed model and algorithm based on several test instances and a real-world case study. The impacts of the quantity of eco-packages, the incentive costs for customers, and the quantity and capacity of recycling stations on the reverse logistics network are explored from both economic and environmental perspectives, providing a reference for practical operation and promotion of eco-packages on a large scale.