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A multi-criteria optimization model for emission-concerned multi-depot vehicle routing problem with heterogeneous fleet

机译:车队异构的排放相关多站点车辆路径问题的多准则优化模型

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Not only greenhouse gases but also other air pollutant emissions from transportation have direct impacts on the environment and human health. The challenge of solving the conflict between profit and environmental consequences in logistics has motivated many studies on the vehicle routing problem. In this paper, a multiobjective mixed integer linear programming model is proposed to minimize transportation expenses and pollutant emissions for the multi-depot heterogeneous vehicle routing problem. A metaheuristic is adapted to obtain the Pareto optimal solutions. After a search procedure, decision makers are able to choose among best transportation plans that balance many objectives at once including economic benefits and environmental impacts. Computational experiments are performed on seven well-known benchmark problem sets. The results demonstrate the existence of greener transportation plans, which are illustrated alongside the best solutions previously reported. The study shows that, in return for a minimal economic tradeoff, a substantial amount of pollution could be avoided.
机译:运输不仅会排放温室气体,还会排放其他空气污染物,直接影响环境和人类健康。解决物流中利润与环境后果之间的冲突的挑战激发了许多关于车辆路径问题的研究。本文提出了一种多目标混合整数线性规划模型,以减少多站点异构车辆路径问题的运输费用和污染物排放。元启发式方法适用于获得帕累托最优解。经过搜索程序,决策者可以在最佳运输计划中进行选择,以同时兼顾包括经济效益和环境影响在内的许多目标。在七个众所周知的基准问题集上进行了计算实验。结果表明存在更绿色的运输计划,并与先前报告的最佳解决方案一起进行说明。研究表明,以最小的经济权衡为代价,可以避免大量的污染。

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