Solving fuzzy job shop scheduling problem based on interval number theory

Abstract

This article discusses the job shop scheduling problem with fuzzy processing time and fuzzy deadline by using interval number theory, which is an efficient method to denote imprecise parameter. Firstly, we convert the original problem to constraint satisfaction problem (CSP) with the assumption that agreement index (AI) is a main optimization objective. Then, the particle swarm optimization (PSO) is merged with genetic algorithm (GA), i.e., an improved particle swarm optimization (IPSO) being used to solve the problem. Finally, the effectiveness of this algorithm is verified by large number of experiments. © 2013 Springer-Verlag.