Eventos Anais de eventos
COBEM 2019
25th International Congress of Mechanical Engineering
Genetic Algorithm to provide a solution in order to minimize makespan and flow time in a flow shop with blocking environment
Submission Author:
Pedro Eduardo Natal , SC
Co-Authors:
Pedro Eduardo Natal, Mauricio Takano, Edson Hideki Koroishi
Presenter: Pedro Eduardo Natal
doi://10.26678/ABCM.COBEM2019.COB2019-1761
Abstract
In this paper, a genetic algorithm (GA) for the flow shop problem considering m-machines, n-jobs, sequence dependent setup time, and zero buffer environment. The objective of this work is to find the best size of the initial population (PS) for the GA algorithm that will minimize the makespan and the total flow time keeping a low computational. Since there isn’t any intermediate storage, a job can be stopped in a machine until the next machine is free, so it is considered to be blocked, and setup time dependent means that according to the sequence chosen setup time can variate between each machine. According to (ZINI,2009), Genetic algorithm is applicable for a wide range of problems and it features good performances, it doesn’t use just local information, therefore it doesn’t get stuck in local minimums, that means it is a good method to be used. The algorithm will be implemented in MATLAB® and will be tested using a 120 problems database. The relative deviation index of the objective function and the mean computational time will be used to compare the best PS for the problem.
Keywords
genetic algorithm, flow shop, Block, makespan, total flow time, scheduling
