Hybrid Branch and Bound Method with Genetic Algorithm for Flexible Flowshop Scheduling Problem

Abstract

This paper considers the multi-stage flexible flowshop scheduling problem to minimize the total completion time. We propose the hybrid branch and bound method with genetic algorithm for flexible flowshop scheduling problem, which provides the exact optimal solution. The genetic algorithm is used to derive an effective upper bound in the bounding scheme to realize the frequent update of current solution, which may cause the reduction of the number of nodes to be searched. The computational efficiency is improved compared with the conventional branch and bound method because of the reduction of the number of searched nodes in spite that the additional computational time for genetic operation.