Application of Latin hypercube sampling in the immune genetic algorithm for solving the maximum clique problem

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Abstract

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. © 2010 Springer-Verlag.

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APA

Benda, Z., & Minghua, C. (2010). Application of Latin hypercube sampling in the immune genetic algorithm for solving the maximum clique problem. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6320 LNAI, pp. 134–141). https://doi.org/10.1007/978-3-642-16527-6_18

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