In order to rationally dispatch logistics distribution vehicles and planning routes,to reduce the costs of logistics management,aiming at the problem of multi-objective route planning in logistics distribution,the optimization scheme based on improved differential evolution algorithm is designed.Logistics distribution path planning involves two optimization objectives,the distance and the vehicle usage;it is a multi-objective optimization type which is different from the standard difference optimization.To achieve the overall goal of cost saving in logistics distribution,based on the analysis of the basic differential evolution algorithm,the real number encoding is applied to the distribution customers. For the multi-objective optimization algorithm,the improvement of mutation operator is proposed to plan the vehicle usage and select the itinerary.By using MATLAB simulation software,the simulation with different initial population shows that the improved differential evolution algorithm converges fast and stable,and achieves the optimization requirements of the multi-objective logistics distribution. By means of multi-objective optimization of logistics distribution,the target of enhancing basic requirements of cost management for logistics enterprises is reached,and it is effectively improves the competitiveness of enterprise in the market economy.%为了合理调度物流配送车辆和规划路程、达到降低物流管理成本的目的,针对物流配送中多目标路径规划问题,利用差分改进算法,设计了优化方案.物流配送路径规划涉及路程和用车量两项优化目标,属于与标准差分优化不同的多目标优化类型.为了达到物流配送节约成本的总体目标,在分析基本差分进化算法的基础上,对配送顾客采用实数编码.针对差分多目标优化算法,提出了通过对变异算子的改进,来规划用车及选择行程.利用MATLAB仿真软件,对不同初始种群进行仿真.仿真结果表明:改进的差分进化算法收敛快而稳定,实现了物流配送多目标的最优化.通过物流配送多目标优化,达到了物流企业提高成本管理的基本要求,有效增强了物流企业在市场经济中的竞争力.
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