不同初始解决方案对单个分配p-hub中心和路由问题的元启发算法的影响
Abdul Kader Kassoumeh1, Zühal Kartal2, Ahmet Arslan1
1Department of Computer Science, Eskisehir Technical University, Eskisehir, Turkiye.
PeerJ. Computer science
|September 24, 2025
概括
本研究介绍了初始化模拟化 (SA) 算法的新方法,以解决复杂的路由问题. 这些策略提高了效率,并为单一分配p-hub中心和路由问题找到更好的解决方案.
科学领域:
- 运营研究 运营研究
- 组合优化的优化.
- 超听证学是一种超听证学.
背景情况:
- 单一分配的p-hub中心和路由问题是具有重大现实应用的NP-hard问题.
- 现有的元启发算法往往难以有效地探索这些复杂问题的搜索空间.
- 高质量的初始解决方案对于像模拟回火这样的元启发式执行至关重要.
研究的目的:
- 开发和评估用于初始化模拟回火 (SA) 算法的新型构造启发式启发式.
- 为了提高单一分配p-hub中心和路由问题的效率和解决方案质量.
- 调查不同初始化策略对SA算法性能的影响.
主要方法:
- 实施各种构造启发式启发式 (贪,混合) 来生成初始解决方案.
- 使用问题分解 (p-hub中心,然后是min-max多个旅行销售员问题) 开发数学方法.
- 将这些初始化方法应用于目标问题的模拟回火 (SA) 算法.
主要成果:
- 每个提出的初始解决方案策略都在具有特定特征的问题实例上取得了改进.
- 马修主义的方法,利用问题的分解,产生了高质量的初始解决方案.
- 对于中大尺寸的测试问题,始终观察到较低的目标函数值.
结论:
- 提出的建设性和数学初始化策略有效地提高了单一分配p-hub中心和路由问题的模拟回火的性能.
- 问题分解和特定领域的知识整合对于产生有效的初始解决方案是有价值的.
- 开发的方法显示了解决NP硬路由和网络设计问题的重大前景.
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