A Multiobjective Genetic Algorithm for Hybrid Flow Shop of a Harddisk Drive’s Manufacturer

Abstract

This paper proposes a solution procedure to solve a scheduling problem of multiobjective hybrid flow shops (HFS). The assembly line of magnetic head operation is composed of several stages of processes. It can be classified as HFS. There are many product families utilizing these assembly line. A constraint of this scheduling is that some models have to be operated in specific parallel machines because of capability of machine and quality issues. The optimization approach namely the preemptive goal programming is employed to solve this scheduling problem. Due to the complexity of the problem, the non-dominated sorting genetic algorithm-II (NSGA-II) is used to search for the solution. The comparison between the optimization and metaheuristic (NSGA-II) is provided. It is found that NSGA-II is more effective in terms of computational times and the quality of solutions. The diversity problem of pareto-optimal solutions is also discussed.