Solving hybrid flowshop scheduling problems by hybrid metaheuristics approach

Flexible flow type production systems, combine flow type systems and parallel machinery systems in a special pattern. In this study, a hybrid Genetic Algorithm Scatter Search metaheuristics method is used in order to solve flexible flowshop scheduling problems by taking into consideration the setup times and lag times. Our goal is to minimize Cmax(makespan), the completion time of all the jobs on the schedule. In this context, firstly a mathematical model studied in the literature is used to solve small instance problems. However the problem we've studied is NP-Hard,for the large instance problems, a hybrid Genetic Algorithm Scatter Search metaheuristics model has been benefited. Results obtained by proposed hybrid algorithm have been benchmarked with the results proposed on the studies in the literature. Proposed hybrid algorithm has given better results than the formerly studied algorithms on 2672 problems amongst 4608 problems on small instances problems and 1276 problems amongst 1536 large instances problems analyzed according to Cmax criterion respectively. Both proposed algorithm and the algorithm proposed in the literature have reached to minimum value on 815 small instances problems. Proposed hybrid algorithm has been compared to Genetic Algorithm for the large instances problems additionally.For larger instances, proposed algorithm has outperformed Genetic Algorithm on 155 problems of 192 problems analyzed according to Cmax(makespan).