A Method for Constructing Genetic Algorithm for a Re-scheduling Problem in an Open-shop Process

Abstract

Recently a new approach is required for a scheduling system which has flexibility against change of condition. This paper deals with re-scheduling for change of the due date, addition of a product, trouble of a machine and increase of processing time, respectively, in an open-shop manufacturing process. For solving this problem, the genetic algorithm (GA) is applied. First a method for constructing GA is proposed for an open-shop problem without change of conditions. By comparing GA with the random search method and the local search method, it is confirmed that the accuracy of GA is better than those of other methods. Secondly, when we solve the re-scheduling problem for change of several conditions, the initial population is revised in such a way that a number of individuals made randomly are added to the population. The effectiveness of the revised algorithm is confirmed through numerical results as compared with the algorithm without revision of the initial population.