改进了鱼群算法,用于解决随着道路状况的变化而出现的物质紧急调度问题
Huawei Jiang1, Shulong Zhang1, Tao Guo1
1College of Information Science and Engineering, Henan University of Technology, Zhengzhou 450001, China.
Mathematical biosciences and engineering : MBE
|September 7, 2023
概括
这项研究引入了改进的鱼群算法,以解决动态道路状况的物质紧急调度挑战. 改进的算法最大限度地降低了分配成本,并比现有方法更有效地减轻了道路状况的影响.
科学领域:
- 运营研究 运营研究
- 计算机科学 计算机科学
- 优化算法 优化算法
背景情况:
- 群算法 (WSA) 在物质紧急调度中面临着局部极端的挑战.
- 动态道路条件使最佳物料分配和车辆路线变得复杂.
研究的目的:
- 提出一个改进的鱼群算法 (IWSA) 用于物质紧急调度.
- 提高算法的处理动态道路状况的能力,避免局部最佳情况.
- 为了最大限度地降低材料分发成本,提高调度效率.
主要方法:
- 一个改进的扫描和克拉克-赖特算法初始化最佳的车辆路径.
- 一个群体移动策略完善了人口更新能力.
- 不同的权重策略扩大了搜索空间,以保持人口多样性.
主要成果:
- 与群系统和自适应混沌遗传算法相比,IWSA表现出优越的性能.
- 该算法有效地将材料分发成本降至最低.
- 改变道路状况对调度的不利影响大大减少.
结论:
- 拟议的IWSA为动态条件下的物质紧急调度提供了强大的解决方案.
- IWSA通过避免局部极端情况和保持人口多样性来提高优化.
- 这种改进的算法提供了一种成本效益和高效的材料分配方法.
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