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arXiv 1107.0055cs.AI
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非对称旅行商问题的相变和主干

Phase Transitions and Backbones of the Asymmetric Traveling Salesman Problem

Washington University in St. Louis(圣路易斯华盛顿大学)

W. Zhang

摘要:

近年来,组合问题中的相变问题引起了人们极大的兴趣。相变已被成功地用于分析组合优化问题,描述其典型情况下的功能和定位的最困难的问题实例。在本文中,我们研究的非对称旅行商问题(ATSP),一个NP-难的组合优化问题,有许多实际应用的相变。使用随机的情况下,多达1,500个城市之间的距离是均匀分布的,我们的经验表明,许多属性的问题,包括最佳的旅游成本和骨干规模,经历急剧转变的精度城际距离增加在一个临界值。我们对ATSP旅行和指派问题的成本的实验结果与指派问题的渐近成本为π ^2 /6且城市数趋于无穷大的理论结果一致。此外,我们发现,著名的分支定界子环消除算法的平均计算成本的问题也表现出颠簸的行为,从容易过渡到困难的距离精度的增加。这些结果积极回答了一个悬而未决的问题,关于ATSP中存在的相变,并提供指导如何困难的ATSP问题的情况下,应产生。

英文摘要:

In recent years, there has been much interest in phase transitions of combinatorial problems. Phase transitions have been successfully used to analyze combinatorial optimization problems, characterize their typical-case features and locate the hardest problem instances. In this paper, we study phase transitions of the asymmetric Traveling Salesman Problem (ATSP), an NP-hard combinatorial optimization problem that has many real-world applications. Using random instances of up to 1,500 cities in which intercity distances are uniformly distributed, we empirically show that many properties of the problem, including the optimal tour cost and backbone size, experience sharp transitions as the precision of intercity distances increases across a critical value. Our experimental results on the costs of the ATSP tours and assignment problem agree with the theoretical result that the asymptotic cost of assignment problem is pi ^2 /6 the number of cities goes to infinity. In addition, we show that the average computational cost of the well-known branch-and-bound subtour elimination algorithm for the problem also exhibits a thrashing behavior, transitioning from easy to difficult as the distance precision increases. These results answer positively an open question regarding the existence of phase transitions in the ATSP, and provide guidance on how difficult ATSP problem instances should be generated.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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