DocumentCode :
617925
Title :
An algorithm based on Evolution Strategies for makespan minimization in hybrid flexible flowshop scheduling problems
Author :
de Siqueira, Eduardo C. ; Souza, Marcone J. F. ; de Souza, Sergio R. ; de Franca Filho, Moacir F. ; Marcelino, Carolina G.
Author_Institution :
Centro Fed. de Educ. Tecnol. de Minas Gerais, Belo Horizonte, Brazil
fYear :
2013
fDate :
20-23 June 2013
Firstpage :
989
Lastpage :
996
Abstract :
This work presents an algorithm based on Evolution Strategies for solving hybrid flexible flowshop scheduling problems. The construction of the initial solution is made by two methods: random NEH heuristic and Iterated Greedy Search metaheuristic. The main search mechanism in the search space of the developed algorithm is mutation, which is based on two parameters, one related to the probability of applying each type of mutation and the other related to the number of times each type of mutation is applied. After carried out the mutation, a portion of the parent population is refined by a local search procedure based on the Iterative Improvement Insertion method. These two versions of the proposed algorithm were tested and the results are compared with the ones from literature. The results showed better solutions for a subset of instances of the problem.
Keywords :
evolutionary computation; flow shop scheduling; greedy algorithms; iterative methods; minimisation; search problems; evolution strategy based algorithm; hybrid flexible flowshop scheduling problems; iterated greedy search metaheuristic; iterative improvement insertion method; local search procedure; makespan minimization; parent population; random NEH heuristic; search mechanism; Job shop scheduling; Minimization; Parallel machines; Sociology; Statistics; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation (CEC), 2013 IEEE Congress on
Conference_Location :
Cancun
Print_ISBN :
978-1-4799-0453-2
Electronic_ISBN :
978-1-4799-0452-5
Type :
conf
DOI :
10.1109/CEC.2013.6557675
Filename :
6557675
Link To Document :
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