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Application of Latin Hypercube Sampling in the Immune Genetic Algorithm for Solving the Maximum Clique Problem

机译:拉丁超立方抽样在解决最大集团问题的免疫遗传算法中的应用

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Based on Latin Hypercube Sampling method, the crossover operation in GA is redesigned; combined with immune mechanism, chromosome concentration is defined and clonal selection strategy is designed, thus an Immune Genetic Algorithm is given based on Latin Hypercube Sampling for solving the Maximum Clique Problem in this paper. The examples shows the new algorithm in solution quality, convergence speed, and other indicators is better than the classical genetic algorithm and good point set genetic algorithm. On the other hand, the new algorithm is not inferior to such classical algorithms as dynamic local search, and it got better solutions to some examples.
机译:基于拉丁超立方体采样方法,对遗传算法中的交叉操作进行了重新设计;结合免疫机制,确定染色体浓度,设计克隆选择策略,提出了基于拉丁超立方抽样的免疫遗传算法,以解决最大集团问题。算例表明,新算法在求解质量,收敛速度等指标上均优于经典遗传算法和优良点集遗传算法。另一方面,新算法并不逊色于动态局部搜索等经典算法,并且对某些示例有更好的解决方案。

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