Solving flow shop scheduling problem using a parallel genetic algorithm

Abstract

The effort of searching an optimal solution for scheduling problems is important for real-world industrial applications especially for mission-time critical systems. In this paper, a parallel GA is employed to solve flow shop scheduling problems to minimize the makespan.According to our experimental results, the proposed parallel genetic algorithm (PPGA) considerably decreases the CPU time without adversely affecting the makespan.