Abstract
Recently a new approach is required for a scheduling system which has flexibility against alteration of problem condition. This paper deals with a multiobjective rescheduling problem in a job shop for alteration of due date. The objectives of this problem are to minimize both the total tardiness and the degree of the change of schedule. The design of genetic algorithm (GA) is proposed for obtaining the Pareto optimal solutions. The initial solutions in the proposed algorithm are generated from the non-dominated solutions in the population obtained for the problem before the alteration. The selection operation is designed so as to choose two solutions from two parents and four offspring generated by means of the crossover operation and the mutation operation. In this operation we introduce a procedure in such a way that not only non-dominated solutions but also solutions to move the population in one direction inferentially are selected. It is confirmed from the computational result that the proposed GA outperforms a local search method and the strength Pareto evolutionary algorithm.
