An effective multi-wave algorithm for solving the max-mean dispersion problem

An effective multi-wave algorithm for solving the max-mean dispersion problem
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求解最大均值色散问题的有效多波算法

DOI:
10.1007/s10732-018-9398-5
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发表时间:
2018-10
影响因子:
2.7
通讯作者:
Punnen Abraham
Punnen Abraham
中科院分区:
计算机科学4区
文献类型:
--
作者:
Song Jiawei;Wang Yang;Wang Haibo;Wu Qinghua;Punnen Abraham

文献摘要

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我们提出了一个有效的多波算法组织在多个搜索阶段的最大均值分散问题,它提供了增强的邻域搜索算法,将持久吸引力的概念,在内存为基础的战略。在每个波中,垂直相位和水平相位首先交替以达到边界解。然后,执行一个结论性的水平阶段,以围绕该边界解进行搜索,以进一步细化解。最后,振荡阶段和多样化的初始解决方案生成阶段侧重于搜索多样化,以建立良好的多样化的初始解决方案,为随后的波和通行证。实验结果表明,所提出的方法执行相当有竞争力的国家的最先进的算法在文献中。额外的分析揭示了所提出的算法中的关键成分的好处。
We propose an effective multi-wave algorithm organized in multiple search phases for the max-mean dispersion problem, which offers enhancement of neighborhood search algorithms by incorporating the notion of persistent attractiveness in memory based strategies. In each wave, a vertical phase and a horizontal phase are first alternated to reach a boundary solution. Then a concluding horizontal phase is executed to search around this boundary solution for further solution refinement. Finally, an oscillation phase and a diversified initial solution generation phase focus on search diversification to build well-diversified initial solutions for subsequent waves and passes. Experimental results show that the proposed approach performs quite competitive with state-of-the-art algorithms in the literature. Additional analysis discloses the benefits of the key ingredients in the proposed algorithm.
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