具有战时随机延误与损耗的多配送中心路径优化

建立了具有战时随机延误与损耗的多配送中心配送路径安排模型,给出了基于随机模拟的蚁群算法。算法通过给定残存率、用时与置信度阈值,把多目标问题作为单目标来处理。用随机模拟的方法来求路径的置信度,并以此为基础搜索转移策略的临域与判断未遍历点的插入位置。算法设计了符合问题特点的从虚拟点出发的转移策略与对两类路段不同的信息素更新策略,确保算法的实现。最后,通过算例说明了该方法的可行性与有效性。

Optimization of Multiple Depots Vehicle Routing Problem with Stochastic Loss and Delay

A model about multiple depots vehicle routing problem with stochastic loss and delay(MDVRPWSL&D) is presented in this paper.And an ant colony algorithm is designed for the model.By setting the value of the remain rate,the cost of time and degree of confidence,the multi-objective problem was transformed into one-objective problem.The way of stochastic stochastic simulation for calculate the degree of confidence,which is used in searching for the border-upon domain and locating the place to insert the demander uncovered.A policy of searching process and two different way of updating the pheromone for two different kinds of routes are described to make sure the realization of the algorithm.On the basis of calculating the example given in this paper,it is shown that the algorithm is reasonable and efficient.