一个离散的野马优化器,用于有能力的车辆路由问题
Chuncheng Fang1,2, Yanguang Cai3, Yanlin Wu3
1School of Automation, Guangdong University of Technology, Guangzhou, 510006, China. fcc_168@163.com.
Scientific reports
|September 11, 2024
概括
一个新的离散野马优化器 (DWHO) 有效地解决了容量化车辆路由问题 (CVRP). 这种增强的算法优于基准测试中的现有方法,为离散优化挑战提供了一种新的方法.
科学领域:
- 运营研究 运营研究
- 计算机科学 计算机科学
- 人工智能的人工智能
背景情况:
- 野生马优化器 (WHO) 是一种对连续工程问题有效的元启发算法.
- 容量车辆路由问题 (CVRP) 是一个复杂的组合优化挑战.
- 现有的CVRP算法在解决方案的精度和质量方面存在局限性.
研究的目的:
- 为CVRP量身定制的野马优化器 (DWHO) 提出一个离散版本.
- 提高世卫组织算法的精度和解决方案质量,以解决离散问题的问题.
- 为了评估DWHO的性能与其他已建立的CVRP算法相比.
主要方法:
- 通过调整WHO原始算法,开发了离散野生马优化器 (DWHO).
- 整合了三个本地搜索策略:交换,反向和插入操作.
- 整合了最大顺序值 (LOV) 解码技术,以改善解决方案表示.
主要成果:
- 在大多数基准实例中,DWHO在与基本的Wild Horse Optimizer (BWHO) 相比,表现出优越的解决能力.
- 实验结果显示,DWHO的性能优于其他算法,如混合火,DSRACO和DAEO.
- 提出的本地搜索和解码技术显著提高了解决方案的精度和质量.
结论:
- DWHO提供了一种新且有效的方法来解决容量车辆路由问题.
- 开发的离散优化框架可以应用于其他复杂的离散问题.
- 整合本地搜索和LOV解码提供了一个强大的方法来提高元启发性能.
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