Intensification-driven tabu search for the minimum differential dispersion problem
Intensification-driven tabu search for the minimum differential dispersion problem
复制标题
集约化驱动的禁忌搜索最小差分色散问题
DOI:
10.1016/j.knosys.2019.01.010
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发表时间:
2019-03
影响因子:
8.8
通讯作者:
Yue Dong
中科院分区:
文献类型:
--
作者:
Lai Xiangjing;Hao Jin Kao;Glover Fred;Yue Dong
The minimum differential dispersion problem is a NP-hard combinatorial optimization problem with numerous relevant applications. In this paper, we propose an intensification-driven tabu search algorithm for solving this computationally challenging problem by integrating a constrained neighborhood, a solution-based tabu strategy, and an intensified search mechanism to create a search that effectively exploits the elements of intensification and diversification. We demonstrate the competitiveness of the proposed algorithm by presenting improved new best solutions for 127 out of 250 benchmark instances (> 50%). We study the search trajectory of the algorithm to shed light on its behavior and investigate the spatial distribution of high-quality solutions in the search space to motivate the design choice of the intensified search mechanism.
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