An Adaptive Immune Genetic Algorithm and Its Application
To avoid premature and guarantee the diversity of the population, an adaptive immune genetic algorithm (AIGA) is proposed to solve these problems. In this method, the AIGA flow structure is presented via combining the immune regulating mechanism and the genetic algorithm. Experimental results showed that the proposed AIGA can rise above efficiently such difficulties of SGA as precocious convergence and poor local search ability and provide well the global converging ability to enhance both global convergency and convergence rate, thus solving effectively the flexible job-shop scheduling problem (FJSP).
flexible job-shop scheduling problem immune genetic algorithm immune operator adaptive strategyvaccine
Gang Shi Gang Shi JiaMa Yuanwei Jing
School of Information Science and Engineeri Northeastern University Shenyang,China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang, China
国际会议
北京
英文
186-189
2010-09-18（万方平台首次上网日期，不代表论文的发表时间）