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Lin-Kernighan heuristic adaptations for the generalized traveling salesman problem

机译:广义旅行商问题的Lin-Kernighan启发式适应

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摘要

The Lin-Kernighan heuristic is known to be one of the most successful heuristics for the Traveling Salesman Problem (TSP). It has also proven its efficiency in application to some other problems. In this paper, we discuss possible adaptations of TSP heuristics for the generalized traveling salesman problem (GTSP) and focus on the case of the Lin-Kernighan algorithm. At first, we provide an easy-to-understand description of the original Lin-Kernighan heuristic. Then we propose several adaptations, both trivial and complicated. Finally, we conduct a fair competition between all the variations of the Lin-Kernighan adaptation and some other GTSP heuristics. It appears that our adaptation of the Lin-Kernighan algorithm for the GTSP reproduces the success of the original heuristic. Different variations of our adaptation outperform all other heuristics in a wide range of trade-offs between solution quality and running time, making Lin-Kernighan the state-of-the-art GTSP local search.
机译:Lin-Kernighan启发式方法是旅行商问题(TSP)中最成功的启发式方法之一。它还证明了其在解决其他一些问题上的效率。在本文中,我们讨论了TSP启发式方法对广义旅行商问题(GTSP)的可能适应,并着眼于Lin-Kernighan算法的情况。首先,我们提供了对原始Lin-Kernighan启发式方法的易于理解的描述。然后,我们提出了一些微不足道的和复杂的改编。最后,我们在Lin-Kernighan改编的所有变体与其他一些GTSP启发式方法之间进行了公平竞争。看来,我们对GTSP的Lin-Kernighan算法的改编再现了原始启发式方法的成功。在解决方案质量和运行时间之间进行广泛的权衡取舍,我们适应的不同变化优于所有其他启发式方法,使Lin-Kernighan成为了最先进的GTSP本地搜索。

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