Using Two Stage Hybrid Algorithm for Solving Flow-Shop Scheduling Problem

The permutation flow shop scheduling is a well-known combinatorial optimization problem that have been widely used and many methods have been used to solve this issue because of their widespread use in the business life market. We reject some hybrid methods in solving these issues by generating a range of issues of different sizes. this paper presents a study on using Ant Colony Optimization (ACO), Genetic algorithm (GA) and their combinations (ACO+GA and GA+ACO) to tackle the FSSP. The computation results show that the two-stage algorithms are able to achieve better results in most cases than ACO and GA individually on the FSSP. The proposed two-stage algorithms and visual layout design system provide an effective tool to solve the practical FSSP.