A hybrid three-phase approach for the Max-Mean Dispersion Problem
A hybrid three-phase approach for the Max-Mean Dispersion Problem
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DOI：
10.1016/j.cor.2016.01.003
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发表时间：
2016-07
期刊：
影响因子：
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通讯作者：
F. D. Croce;Michele Garraffa;F. Salassa
中科院分区：
文献类型：
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作者：
F. D. Croce;Michele Garraffa;F. Salassa
本文讨论的最大平均分散问题（最大平均DP）属于一般类别的聚类问题，其目的是找到一个子集的集合，最大限度地提高了分散/元素之间的相似性的措施。提出了一种三阶段混合启发式算法，该算法结合了混合整数非线性求解器、局部分支方案和路径重连过程。对文献实例的计算结果表明，所提出的方法优于国家的最先进的方法。
This paper deals with the Max-Mean Dispersion Problem (Max-Mean DP) belonging to the general category of clustering problems which aim to find a subset of a set which maximizes a measure of dispersion/similarity between elements. A three-phase hybrid heuristic was developed, which combines a mixed integer non-linear solver, a local branching scheme and a path relinking procedure. Computational results performed on the literature instances show that the proposed procedure outperforms the state-of-the-art approaches.