Minimizing Makespan In Permutation Flow Shop Scheduling Problems Using A Hybrid Metaheuristic Algorithm

摘要

This paper proposes a hybrid metaheuristic for the minimization of makespan in permutation flow shop scheduling problems.The solution approach is robust,fast,and simply structured,and comprises three components: an initial population generation method based on a greedy randomized constructive heuristic,a genetic algorithm (GA) for solution evolution,and a variable neighbourhood search (VNS) to improve the population.The hybridization of a GA with VNS,combining the advantages of these two individual components,is the key innovative aspect of the approach.Computational experiments on benchmark data sets demonstrate that the proposed hybrid metaheuristic reaches high-quality solutions in short computational times.Furthermore,it requires very few user-defined parameters,rendering it applicable to real-life flow shop scheduling problems.