A genetic algorithm for solving a hybrid flexible flowshop with sequence dependent setup times

In this paper, we propose a genetic algorithm (GA) to solve a realistic variant of flowshop problem. The variant considered here is a hybrid flexible flowshop problem with sequence-dependent setup times, and with the objective of minimizing the makespan. This type of flowshop is frequently used in the batch production, helping toreduce the gap between research and operational use. The proposed approach introduces three new crossover operators. Numerical experiments compare the performance of the GA on different benchmarks from the literature. The results show that the proposed approach is more effective than all other adaptations.