基于杂合机制的免疫遗传算法在动态问题中的应用

针对遗传算法在求解动态问题时存在多样性缺失，无法快速响应环境变化的问题，提出一种基于杂合子机制的免疫遗传算法．该算法借鉴免疫系统中多样性与记忆机理，从保持等位基因多样性出发，在免疫变异中引入杂合映射机制，使种群能够探索更大的解空间．同时，通过引入记忆策略，使算法迅速跟踪最优解变化轨迹．该方法在动态０-１优化问题的求解中取得了较好的效果．

Heterozygosis-based immune genetic algorithm for dynamic optimization problems

In order to prevent the diversity loss and enhance the adaptation capacity for genetic algorithm in dynamic environments, a heterozygosis-based immune genetic algorithm is proposed for solving dynamic problem. Inspired by the diversification and memory mechanisms in the immune system, for the purpose of maintaining diversity of allies, a heterozygosis-based mapping operator is introduced in the process of immune mutation, which helps individuals to explore the search space comprehensively. Meanwhile, a memory-based scheme is introduced to speed up the reaction to the moving optima. The proposed algorithm is applied to the dynamic 0-1 optimization problems with promising results.