An Adaptive Differential Evolution Algorithm for Flow Shop Scheduling to Minimize Makespan

This paper proposed an adaptive differential evolution algorithm. The algorithm has an adaptive mutation factor which can be nonlinear reduced along with evolution process. Mutation factor is declined slowly in the beginning of evolution process in order to improve the global searching ability of the algorithm, and declined rapidly in the later of evolution process. The proposed algorithm is applied to solve flow shop scheduling to minimize makespan, computational experiments on a typical scheduling benchmark shows that the algorithm has a good performance.