摘要
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。
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.
出处
《常州工学院学报》
2014年第5期21-26,共6页
Journal of Changzhou Institute of Technology
基金
2013年国家级大学生创新创业训练计划项目(201310363042)
国家自然科学基金资助项目(51305001)
关键词
免疫系统
粒子群算法
排样优化
immune system
particle swarm optimization
packing optimization
