An Hybrid Genetic Algorithm to Optimization of Flow Shop Scheduling Problems under Real Environments Constraints

Abstract

This paper aims to analyzing the effect of the inclusion of several constraints that have negative influence in the real manufacturing productions. For the solution of the scheduling problem treated in this paper, known as Flow Shop Scheduling, an efficient Genetic Algorithm is introduced combined with the Variable Neighborhood Search for problems of n tasks and m machines minimizing the total completion time or makespan. Release date, dependent setup-times and transport times are entered. These are common restrictions that can be found in multiple manufacturing environments where there are machines, tools, and a set of jobs must be processed in these, following the same flow pattern. The computational experiments carried out on a set of instances of problems of different sizes of complexity show that the proposed hybrid metaheuristic achieves high quality solutions comparable to the optimum ones reported.