Comparison of metaheuristics for solving the bi-objective flexible job shop problem
International Conference on Metaheuristics and Nature Inspired Computing
This paper deals with a problem of flexible job shop (FJSP) with the objective of minimising makespan and production just in time. This FJSP is known to be NP-hard. Our objective is to optimize both criteria simultaneously. For this, we selected ve known ecient methods of multi-objective optimization (NSGAII, SPEAII, KBACO, PDABC and AIS) to get the Pareto optimal. For the purpose of performance evaluation of our proposed algorithms, we generate some instances. Also a comprehensive computational is conducted in order to analyse the performance of the applied algorithms in four metrics including the hyper-volume or H-metric, the coverage of two Pareto fronts "C-Metric", the spacing measure and the absolute metric Hole Relative Size (HRS) measures the size of the largest hole in the space of solutions of the Pareto front are presented. The results indicate that NSGA-II has had a better performance in comparison with the other four algorithms.