A Remanufacturing Logistics Network Model Based on Improved Multi-objective Ant Colony Optimization

Abstract

This paper attempts to optimize the location selection of processing centers, vehicle routing and carbon emissions in the remanufacturing logistics network. For this purpose, the author developed a novel optimization model to minimize the total cost of remanufacturing logistics, and designed an improved multi-objective ant colony optimization (MACO) algorithm to solve the model. The simulation results show the effectiveness and efficiency of our algorithm in solving the optimization problem. The research findings provide a reference for reducing reverse logistics cost considering environmental factors.