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GRASP and path relinking for the max-min diversity problem

机译:GRASP和路径重新链接解决最大-最小分集问题

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摘要

The max-min diversity problem (MMDP) consists in selecting a subset of elements from a given set in such a way that the diversity among the selected elements is maximized. The problem is NP-hard and can be formulated as an integer linear program. Since the 1980s, several solution methods for this problem have been developed and applied to a variety of fields, particularly in the social and biological sciences. We propose a heuristic method-based on the GRASP and path relinking methodologies-for finding approximate solutions to this optimization problem. We explore different ways to hybridize GRASP and path relinking, including the recently proposed variant known as GRASP with evolutionary path relinking. Empirical results indicate that the proposed hybrid implementations compare favorably to previous metaheuristics, such as tabu search and simulated annealing.
机译:最大最小分集问题(MMDP)在于从给定集合中选择元素子集,以使所选元素之间的差异最大化。这个问题是NP问题,可以表述为整数线性程序。自1980年代以来,针对此问题的几种解决方法已经开发出来,并应用于各种领域,特别是在社会和生物科学领域。我们提出了一种基于GRASP和路径重新链接方法的启发式方法,用于找到该优化问题的近似解决方案。我们探索了将GRASP与路径重新链接混合的不同方法,包括最近提出的带有进化路径重新链接的GRASP变体。实验结果表明,所提出的混合实现方式与禁忌搜索和模拟退火等先前的元启发法相比具有优势。

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