Genetic Algorithms for Bi-Objective Job Shop Scheduling Problem
Moreira, M.C.O.
Arroyo, J.E.C.
Januario, T.O.
Oliveira, P.L.
Dept. de Inf., Univ. Fed. de Vicosa, Vicosa;
This paper appears in: Hybrid Intelligent Systems, 2008. HIS '08. Eighth International Conference on
Publication Date: 10-12 Sept. 2008
On page(s): 720-725
Location: Barcelona,
ISBN: 978-0-7695-3326-1
INSPEC Accession Number: 10234631
Digital Object Identifier: 10.1109/HIS.2008.43
Current Version Published: 2008-09-19
Abstract
This article considers the bi-objective job shop scheduling problem in which the make span and the total tardiness of jobs are minimized. In order to find a set of dominant solutions, that is, an approximation of the Pareto optimal solutions, we propose three versions of a genetic algorithm with techniques like hybridization with local search, path relinking and elitism. The three versions of the algorithm are compared with each other and they are also compared with other multiobjective genetic algorithm proposed in the literature.
Index
Terms
Available to subscribers and IEEE members.
References
Available to subscribers and IEEE members.
Citing Documents
Available to subscribers and IEEE members.
Cart
