A simulation-optimization system for recycling logistics network of recyclable express packaging

• Published in: Computers & industrial engineering Vol. 189; p. 109949
• Main Authors: Shi, Yuhe, Lin, Yun, Wang, Songyi, Wen, Haolin, Yang, Lili, Lim, Ming K., Li, Yan
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.03.2024
• Subjects: Agent-based modeling; Location routing problem; Recyclable express packaging; Recycling logistics network; Simulation-optimization method; Agent-based modeling; Simulation-optimization method; Recyclable express packaging; Recycling logistics network; Location routing problem
• ISSN: 0360-8352; 1879-0550
• DOI: 10.1016/j.cie.2024.109949

[Display omitted] •Proposed the covering location routing problem in a reverse logistics network.•New network features include facility function overlap and reverse time window.•Designed a simulation-optimization method with a hybrid heuristic.•The experiments verified the effectiveness and stability of the system.•The results highlighted the service trade-off between facility and vehicle. To promote the adoption of recyclable express packaging (REP), this paper focuses on providing a realistic simulation-optimization system for establishing an efficient, green, and economical REP recycling logistics network by integrating optimization methods and agent-based techniques. The planned solution encompasses decisions related to facility location, service planning, and vehicle routing. The designed hybrid heuristic algorithm aims to independently find optimal solutions for subproblems while considering the interactions among these subproblems, in which the improved global solutions can be uncovered through alternating multi-stage local searches. The numerical experiments highlight the significant importance of the interactions among multi-stage search strategies. A crucial trade-off between facility service quantity and vehicle service quantity within the logistics network is indispensable to explore improved global solutions. From the perspective of reducing operating costs, a larger service capacity range for recycling stations is preferable. However, this cost optimization without increasing the number of vehicles entails some time costs. Additionally, the results suggest that the optimal number of the opened recycling station is the value that enables the total covering percentage of demand points to be between 75 % and 82 %, which provides valuable decision guidance for recycling network planning.