An application of immune genetic algorithm for flexible job-shop scheduling problem

The flexible job-shop scheduling problem (FJSP) is one of the most general and difficult of all traditional scheduling problem. The paper presents a novelty immune genetic algorithm (IGA) to solve the problem. This algorithm preserves the random global search ability of simple genetic algorithm (SGA), and introduces the immune mechanism by which the necessary vaccine may be extracted with the scheduling vaccinated so as to improve efficiently SGA´s low ability for global search because of immature convergence and low local search ability. Thus, the IGA proposed can provide such ability and convergence rate that will implement the global optimum solution. The computation results validate the effectiveness of the proposed algorithm .