软时间窗和匹配运输下的供应链配送网络优化

Distribution Network Optimization of Supply Chain under Constraints of Matching Transportation and Soft Time Windows

针对客户和供应商匹配运输下的供应链配送网络优化问题,在模型中加入客户软时间窗约束、车辆最大行驶距离约束以及设施容量约束,建立了全新的0-1整数规划模型,采用基于整数编码和交换序的离散粒子群优化算法来求解。通过算例将标准粒子群算法(PSO)、局部版粒子群算法(LPSO)和离散粒子群算法(DPSO)的运行结果进行比较,结果表明,DPSO算法可以减少迭代次数,并获得问题的最优解。

A new distribution network optimization problem in the supply chain background was studied. In the design of transportation network we adopted the matching mode in which a supplier and a customer are merged. The model was built with soft time windows constraint, vehicle maximum driving distance constraint and capacity constraints. Discrete particle swarm optimi- zation algorithm based on integer number coding and random swap sequence was applied to solve the problem. Finally the validity of the model and the algorithm was tested through operating and comparing three different algorithms on numerical examples. Resuits show that DPSO can reduce the iteration number, and get the optima/solution of the problem.