Designing sustainable logistics networks for classified municipal solid wastes collection and transferring with multi-compartment vehicles

Abstract

The success stories of waste classification and processing systems in reducing emissions and conserving natural resources have inspired many countries to adopt similar systems. The current research on waste collection logistics network design is limited in capturing the features of waste classification systems. The environmental objectives, the use of multi-compartment vehicles to separate waste and reduce driving distance, and the joint decision-making of transfer station locations and vehicle routes are not integrated into the same optimization framework. This study aims to investigate the strategic planning of transfer stations and vehicle fleet dispatch in a city-level classified waste collection system. The problem is formulated as an integer programming problem that minimizes total travel costs while considering greenhouse gas (GHG) emissions. To solve the problem effectively, we propose a fast hybrid heuristic algorithm based on column generation (CG) and Adaptive Large Neighborhood Search (ALNS). The proposed algorithm framework is tested on various instances and applied to a real-sized logistics network in Chengdu, China. Computational results indicate that the proposed algorithm achieves high efficiency while maintaining a satisfactory gap. The results confirm that introducing the waste classification system can help reduce total travel costs and greenhouse gas emissions.