Optimization of Flow Shop Scheduling Problem Using Differential Evolution and Variable Neighborhood Search

Abstract

This paper proposed a new differential evolution algorithm based on variable neighbourhood search which is called as VNSDE. In VNSDE, the operation of variable neighbourhood search is performed after three basic operations of differential evolution, which can enhance the global search and improve the convergence. VNSDE is applied for solving flow shop scheduling problem with the makespan criterion. Computational experiment is performed over a typical FSSP benchmark using VNSDE, GA and DE, and result shows that VNSDE has higher performance than GA and DE.