Improved immune genetic algorithm based on Latin hypercube sampling
一种改进拉丁方抽样免疫遗传算法*

Aiming at the defects of Genetic Algorithm(GA) in the deficiency of keeping population diversity, prematurity, time-consuming, low success rate and so on, the crossover operation in GA is redesigned by Latin Hypercube Sampling. 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 in this paper. The Traveling Salesman Problem and the Maximum Clique Problem were used to verify the new algorithm, 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.