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

Received: 28 March 2019 Accepted: 10 July 2019 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.

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