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A binary multi-verse optimizer algorithm applied to the set covering problem

机译:一种应用于集覆盖问题的二进制多诗词优化器算法

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Many problems addressed in operational research are combinatorial and NP-hard type. Therefore, designing binary algorithms based on swarm intelligence continuous metaheuristics is an area of interest in operational research. In this paper we use a general binarization mechanism based on the percentile concept. We apply the percentile concept to multi-verse optimizer algorithm to solve set covering problem (SCP). Experiments are designed to demonstrate the utility of the percentile concept in binarization. Additionally we verify the efficiency of our algorithm through benchmark instances, showing that Binary multi-verse Optimizer (BMVO) obtains adequate results when it is evaluated against another state of the art algorithm.
机译:运筹学中解决的许多问题是组合型和NP-hard型。因此,设计基于群体智能连续元启发式算法的二进制算法是运筹学中一个感兴趣的领域。在本文中,我们使用基于百分位数概念的通用二值化机制。我们将百分位数概念应用于多诗词优化器算法,以解决集合覆盖问题(SCP)。实验旨在证明百分位数概念在二值化中的实用性。此外,我们通过基准测试实例验证了我们算法的效率,表明当对另一种最新算法进行评估时,二进制多宇宙优化器(BMVO)获得了足够的结果。

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