Integrated production scheduling and maintenance planning in a hybrid flow shop system: a multi-objective approach

Abstract

This study deals with a hybrid flowshop system with sequence-dependent setup times. Two objectives have been considered. Minimizing makespan for production purpose along with minimizing unavailability of the system for maintenance purpose are the objectives of this problem. Two meta-heuristics have been developed for the research problem. First one is a non-dominated sorting genetic algorithm-II (NSGA-II), while the second one is a hybridized NSGA-II (HNSGA-II), which is accompanied by a local search procedure to create better results. These two algorithms allow the decision maker to find compromise solutions between production objectives and preventive maintenance ones. Two decisions should be taken at the same time: finding the best assignment and sequence of jobs on machines in order to minimize the makespan, and deciding how often to perform preventive maintenance actions in order to minimize the system unavailability. Three approaches have been suggested for evaluation and comparison the efficiency of algorithms. The results indicate that the HNSGA-II presents better solutions compared to the ordinal NSGA-II in terms of objective functions viewpoint, while the results are obviously reversed in balance degree of achieving both objectives simultaneously.