最小独立支配集问题的有效局部搜索

Kazuya Haraguchi
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引用次数: 0

摘要

本文给出了求解最小独立支配集问题的一种有效的局部搜索方法。我们考虑使用k-swap作为邻域操作的局部搜索。给定一个可行解S,它是通过从S中去掉恰好k个顶点,然后添加任意数量的顶点来获得另一个可行解的操作。我们证明,当k=2时,(p。, k=3且给定解相对于2-swap是最小的),我们可以在邻域内找到一个改进解或得出在O(n\Delta) (resp)中不存在这样的解的结论。, O(n\Delta^3))时间,其中n表示顶点数,\Delta表示最大度。我们开发了一种元启发式算法,迭代地重复提出的局部搜索和平台搜索。该算法非常有效,它更新了九个DIMACS图的最著名的上界。
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An Efficient Local Search for the Minimum Independent Dominating Set Problem
In the present paper, we propose an efficient local search for the minimum independent dominating set problem. We consider a local search that uses k-swap as the neighborhood operation. Given a feasible solution S, it is the operation of obtaining another feasible solution by dropping exactly k vertices from S and then by adding any number of vertices to it. We show that, when k=2, (resp., k=3 and a given solution is minimal with respect to 2-swap), we can find an improved solution in the neighborhood or conclude that no such solution exists in O(n\Delta) (resp., O(n\Delta^3)) time, where n denotes the number of vertices and \Delta denotes the maximum degree. We develop a metaheuristic algorithm that repeats the proposed local search and the plateau search iteratively. The algorithm is so effective that it updates the best-known upper bound for nine DIMACS graphs.
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