摘要：AbstractThe concept of green logistics stems from green economic concepts which are inherently driven by the environmental sustainability challenges. In this work, measures of carbon dioxide (CO2) emission are added to the canonical capacitated vehicle routing problem. The proposed multi-objective optimization model tackles the conflicting objectives of the emission reduction while holding-off the economic cost uplift, leading to a set of Pareto optimal solutions. A biologically inspired Ant Colony Optimization (ACO) based evolutionary constructive heuristic is used to obtain routing plans with minimum financial impact. A Variable Neighborhood Search (VNS) algorithm is designed to obtain low emission routes by exploring the neighborhood of the ant foraging paths. The hybrid ACO-VNS heuristic will provide a set of non-dominated solutions leading to the Pareto optimal solution frontier. For consistency of solutions and solution convergence, the algorithm is tested on randomly generated problem instances.
