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arXiv 1402.1379cs.DScs.NE
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二次最小生成树问题的三阶段搜索法

A Three-Phase Search Approach for the Quadratic Minimum Spanning Tree Problem

Zhang-Hua Fu, Jin-Kao Hao

摘要:

给定一个无向图,每个边和每对边都有代价,二次最小生成树问题(QMSTP)包括确定一棵总代价最小的生成树。这个问题可以用来模拟许多现实生活中的网络设计应用程序,其中路由和干扰成本都应考虑。针对这个问题,我们提出了一种名为TPS的三阶段搜索方法,该方法集成了1)基于下降的邻域搜索阶段,使用两个不同的移动算子从给定的起始解到达局部最优值,2)局部最优值探索阶段,在给定的区域搜索区域内发现附近的局部最优值,以及3)基于扰动的多样化阶段,跳出当前的区域搜索区域。此外,我们引入专用技术来减少邻域,以探索和简化邻域评估。基于数百个代表性基准的计算实验表明,TPS通过改进31个实例的最佳已知结果和匹配的最佳已知结果,除了两种情况下,其余的实例产生高度竞争力的结果相对于在文献中的最佳性能的方法。所提出的算法的关键要素进行了分析。

英文摘要:

Given an undirected graph with costs associated with each edge as well as each pair of edges, the quadratic minimum spanning tree problem (QMSTP) consists of determining a spanning tree of minimum total cost. This problem can be used to model many real-life network design applications, in which both routing and interference costs should be considered. For this problem, we propose a three-phase search approach named TPS, which integrates 1) a descent-based neighborhood search phase using two different move operators to reach a local optimum from a given starting solution, 2) a local optima exploring phase to discover nearby local optima within a given regional search area, and 3) a perturbation-based diversification phase to jump out of the current regional search area. Additionally, we introduce dedicated techniques to reduce the neighborhood to explore and streamline the neighborhood evaluations. Computational experiments based on hundreds of representative benchmarks show that TPS produces highly competitive results with respect to the best performing approaches in the literature by improving the best known results for 31 instances and matching the best known results for the remaining instances only except two cases. Critical elements of the proposed algorithms are analyzed.

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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