车辆路径matlab代码-Intelligent_Algorithm:优化问题解决:遗传算法,蚁群算法,禁忌搜索算法,模拟退火算法,粒子群优化

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车辆路径 matlab代码 Intelligent_Algorithm 用matlab解决路径规划和竞争设施选址问题 一、五个基础算法以及示例: ga 遗传算法解决分配问题 问题描述: 现有10个工人去做10件工作,每个工人完成每项工作所需时间不同。 要求每个工人只做一项工作,每项工作只由一个工人完成。 怎样指派工人完成工作可以使所用总时间最少? tabu 禁忌搜索算法解决解决商旅问题 问题描述: 某5个城市旅行商问题, 用禁忌搜索算法实使得旅行商走过所有城市后回到原点的总路径最小。 ants 蚁群算法 问题描述: 设有19个客户随机分布于长为10km的正方形区域内。配送中心位于区域正中央,其坐标为(0,0)。 各客户的坐标及需求量如下表所示,配送中心拥有若干辆载重量为9t的车辆,对客户进行服务时都从配送中心出发, 完成对客户点的配送任务后再回到配送中心。现要求以最少的车辆数、最小的车辆总行程来完成货物的派送任务, 用蚁群算法求解该VRP问题(vehicle routing problem)。 SA 模拟退火算法 问题描述: n 个工作将要指派给n 个工人分别完成,问如何安排可使总的

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