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). © 2012 Springer-Verlag Berlin Heidelberg