一种基于集体智能的新方法来解决旅行销售员的问题
Mustafa Servet Kiran1, Mehmet Beskirli2
1Department of Computer Engineering, Konya Technical University, 42250 Konya, Türkiye.
Biomimetics (Basel, Switzerland)
|February 23, 2024
概括
本研究介绍了一种新的系统算法,用于离散优化问题,通过路径构建和改进来增强解决方案. 新的足迹机制提高了解决方案的质量,在旅行销售员问题上取得了可比的结果.
科学领域:
- 计算智能是一种计算智能.
- 运营研究 运营研究
- 计算机科学 计算机科学
背景情况:
- 离散优化问题在各种科学和工业领域普遍存在.
- 现有的算法在有效地找到最佳解决方案方面可能面临挑战.
- 集体智能方法为新的优化策略提供了潜力.
研究的目的:
- 介绍一种基于系统算法的新型离散优化方法.
- 引入一个足迹机制,以加强解决方案构建中的集体智能.
- 评估关于旅行销售员问题的拟议方法的性能.
主要方法:
- 拟议的方法整合了路径建设,路径改进和足迹机制.
- 集体智能指导在路径建设阶段创建解决方案.
- 社区运营完善解决方案,并使用特定问题的数据平衡选择概率.
主要成果:
- 系统算法在25个旅行销售员问题上进行了测试.
- 性能与最先进的算法进行了比较.
- 拟议的方法显示了与现有算法可比的结果.
结论:
- 新系统方法有效地解决了离散优化挑战.
- 足迹机制增强了系统找到高质量的解决方案的能力.
- 该方法在解决复杂的优化任务方面表现有前途,例如旅行销售员问题.
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