基于集成定位-运输路线安排问题的废旧家电逆向回收物流网络优化

Reverse logistic networks optimization of home appliances return based on combined location routing problem

针对废旧家电逆向回收物流成本高、效益差而导致其回收率低的问题,提出一种应用离散微粒群智能算法优化废旧家电逆向回收物流网络模型的方法。在系统分析废旧家电逆向回收物流网络结构与要素基础上,构建基于集成定位-运输路线安排问题的废旧家电逆向回收物流网络优化模型,引入随机交换序与部分映射交叉(PMX)算子使离散微粒群优化(DPSO)算法具备良好的全局及局部搜索能力,来对该模型进行智能优化与求解。实例仿真结果表明,通过该优化模型及算法得到的全局最优解具有良好的收敛性和有效性;同时,能有效降低废旧家电逆向回收物流运作总成本。

Concerning the low recovery rate caused by high costs and low margins of the reverse logistics of the waste home appliances, the paper put forward a method which adopted the application of Discrete Particle Swarm Optimization （DPSO） to optimize the reverse logistics network model of the waste home appliances. After analyzing the structure and elements of the reverse logistics network model of the waste home appliances based on integrated location-routing problem, random swap sequence and Partially Mapped Crossover （PMX） operator were introduced to make DPSO possess overall and partial searching ability for intelligently optimizing and solving the model. The simulation results illustrate that the globally optimal solution achieved through this optimization model and algorithm has good convergence and effectiveness, at the same time, it can reduce the total cost of reverse logistics of the waste home appliances effectively.