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arXiv cs/0212044cs.DS
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用“难”问题近似“易”问题:最大匹配和最大旅行商问题的启发式算法

Solving a "Hard" Problem to Approximate an "Easy" One: Heuristics for Maximum Matchings and Maximum Traveling Salesman Problems

Sandor P. Fekete, Henk Meijer, Andre Rohe, Walter Tietze

摘要:

我们考虑几何实例的最大加权匹配问题(MWMP)和最大旅行商问题(MTSP)与多达300万顶点。利用MWMP,MTSP,和费马韦伯问题(FWP)之间的几何对偶关系,我们开发了一种启发式方法,产生近线性时间的解决方案以及上界。使用各种计算工具,我们得到的解与最优解的偏差远小于1%。我们的方法的一个有趣的特点是,即使一个FWP是很难计算的理论和埃德蒙兹的算法最大加权匹配产生一个多项式的解决方案的MWMP,实际行为恰恰相反,我们可以解决FWP以高精度,以找到一个很好的启发式解决方案的MWMP。

英文摘要:

We consider geometric instances of the Maximum Weighted Matching Problem (MWMP) and the Maximum Traveling Salesman Problem (MTSP) with up to 3,000,000 vertices. Making use of a geometric duality relationship between MWMP, MTSP, and the Fermat-Weber-Problem (FWP), we develop a heuristic approach that yields in near-linear time solutions as well as upper bounds. Using various computational tools, we get solutions within considerably less than 1% of the optimum. An interesting feature of our approach is that, even though an FWP is hard to compute in theory and Edmonds' algorithm for maximum weighted matching yields a polynomial solution for the MWMP, the practical behavior is just the opposite, and we can solve the FWP with high accuracy in order to find a good heuristic solution for the MWMP.

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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