探索一个有利的权衡,在大规模网络中找到每个有效路径
IEEE transactions on cybernetics
|March 4, 2025
概括
本研究介绍了一种新的算法,以有效地解决大型网络中的多目标最短路径问题 (MSPP). 它解决了决策者的偏好,并减少了计算开销,以更好地优化网络.
科学领域:
- 网络优化 网络优化
- 算法开发 算法开发
- 计算机科学 计算机科学
背景情况:
- 多目标最短路径问题 (MSPP) 对于网络优化至关重要,但在大型网络中面临着不同的决策者偏好和高计算成本的挑战.
- 现有的方法难以平衡相互冲突的目标,并管理解决大规模网络的MSPP固有的时空开销.
研究的目的:
- 在大规模网络中开发MSPP的通用算法,以适应不同决策者的偏好.
- 显著减少与解决MSPP相关的时空空间开销,使其更适用于现实世界的应用.
主要方法:
- 介绍一个新概念:普遍的统治关系.
- 使用通用动态编程方法开发一个通用的多目标最短路径算法.
- 应用可减少H的技术来加速算法收.
主要成果:
- 拟议的算法成功地在可容忍的时间框架内找到所有有效路径.
- 严格的证明证实了算法的处理不同偏好的能力,并实现低的时空开销.
- 大规模通信网络上的实验结果证明了算法的有效性和竞争力.
结论:
- 开发的通用MSPP算法为大规模网络优化问题提供了有效的解决方案.
- 该方法满足了决策者的不同偏好,同时保持了低计算复杂度.
- 该算法的在温和假设下分布式实现的潜力进一步提高了其适用性.
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