数学建模优化物流运输路径可行解的改进算法及其应用

Mathematical Modeling and Improved Algorithm for Feasible Solution of Logistics Transportation Route Model and Its Application

针对带时间窗物流运输最优化路径选择问题,基于概率分布算理的共同机制,将遗传算法全局搜索优势与模拟退火算法局部搜索优势有机整合,有效规避二者算法寻优性能的不足,使构建的改进算法兼顾优越的全局搜优能力和计算效率。针对9个目标点物流运输路径优化问题的可行解,展开算法应用的试验验证。结果显示,若目标点数量较少能够求得最优解,若目标点数量较多则能够求得满意解。

In this paper, in view of the logistics transportation route optimization problem with time window and based on the common mechanism of the probabilistic distribution principle, we integrated the genetic algorithm with the strength of global searching and the simulated annealing algorithm which exceled in local searching and then in the numerical example of a logistics transportation route problem with nine destination points, demonstrated and validated the algorithm.