基于免疫原理的粒子群排样优化方法

针对排样优化中种群个体多样性保持及全域寻优存在的问题，将免疫系统的免疫信息处理机制引入到粒子群优化算法中，建立求解排样问题的粒子群免疫优化方法。该方法借鉴人工免疫中抗体的多样性保持机制及免疫记忆功能，强调优势基因的进化和浓度稳定，提高了算法的全域搜索速度并保持了群体多样性。实验表明，在对船舶不规则件排样优化问题求解中，免疫机制对粒子群优化的最优搜索具有较好的有效性和较高的可行性。

Immune-based Solution to Particle Swarm Optimization Packing Problem

The immune information processing mechanism of immune system was involved into particle swarm optimization（ PSO） for diversity of individuals and populations globally optimizing.The paper estab-lished immune PSO method solving packing problem.The proposed algorithms have both the mechanisms properties to maintain diversity of antibodies and the immune memory function,which emphasized the advan-tages of genetic evolution and concentration stability,and improve the global evolution speed and population diversity.Its effectiveness has been fairly proved in practice for hull irregular parts packing optimization.