混合模拟植物生长算法在包装件配送中的应用

目的针对改进模拟植物生长算法(IPGSA)容易陷入局部最优解及其算法运行时间较长,提出混合模拟植物生长算法(HPGSA)来求解带时间窗车辆调度问题(VSPTW)。方法在IPGSA基础上,提出求解包装件物流配送中VSPTW的混合模拟植物生长算法(HPGSA)。改进IPGSA初始调度方案的构造方式,设计求解VSPTW的C-W算法用于构造HPGSA的初始调度方案;改进IPGSA的邻域搜索算子,选择插入搜索算子和互换搜索算子对HPGSA进行邻域搜索;对18个不同规模的Solomon算例进行仿真测试。结果相对于其他智能算法,HPGSA具有更好的求解性能,能够保证VSPTW对求解算法的要求。结论 HPGSA的全局优化能力、稳定性和运行速度均优于IPGSA、遗传算法、蚁群算法和禁忌搜索算法。

Application of Hybrid Plant Growth Simulation Algorithm in Packaged Products Distribution

This work was aimed to improve the performance of improved plant growth simulation algorithm (IPGSA) to solve vehicle scheduling problem with time windows (VSPTW). Based on IPGSA, a hybrid simulation PGSA (HPGSA) was proposed to solve VSPTW in the logistics distribution of packaged products. Firstly, the method in IPGSA to produce initial scheduling scheme was improved, and the C-W algorithm was designed and solved to construct the initial scheduling scheme of HPGSA. Secondly, the neighborhood search operator of IPGSA was improved, and the insert and swap search operators were selected to carry out the neighborhood search of HPGSA. Finally, a simulation test was carried out on 18 Solomon cases at different scales. Compared with other intelligent algorithms, HPGSA had better performance and could guarantee the requirement of VSPTW. The global optimization ability, stability and running speed of HPGSA were better than IPGSA, genetic algorithm, ant colony algorithm and tabu search algorithm.