Bi-level multi-objective optimization for the vehicle routing problem from a waste-to-energy reverse logistics network

Abstract

Given the considerable economic and environmental challenges posed by kitchen waste, this paper proposes a reverse logistics network equipped with four potential transportation and treatment technologies to achieve efficient waste reduction and energy recovery. A bi-level multi-objective optimization model is developed to address the vehicle routing problem derived from the network. The upper-level local authority aims to minimize fiscal expenditure and carbon emissions by determining subsidy amounts and carbon emission quotas. The lower-level kitchen waste operator seeks to maximize total profits by determining vehicle routes and waste loading amounts. The proposed model incorporates technology parameters, enabling decision makers to assess waste-to-energy efficiency across different technology combinations. The model is applied to a real-life case study in China, and the calculation results and sensitivity analyses provide key insights: (1) The combination of diesel trucks and black soldier fly technology currently yields the highest economic profits, with the operator independently generating 41% of its profits; (2) Under the optimal technology combination, raising the resource utilization rate can further enhance waste-to-energy performance and boost the operator’s economic profits; (3) Expanding truck capacity can increase the operator’s economic profits without adding to the fiscal burden on the local authority.