International Journal of Computational Intelligence Systems

Volume 1, Issue 2, June 2008, Pages 134 - 147

An application of effective genetic algorithms for Solving Hybrid Flow Shop Scheduling Problems

Authors
Cengiz Kahraman, Orhan Engin, Ihsan Kaya, Mustafa Kerim Yilmaz
Corresponding Author
Cengiz Kahraman
Available Online 12 June 2008.
DOI
https://doi.org/10.2991/ijcis.2008.1.2.4How to use a DOI?
Keywords
Hybrid flow shop scheduling, Genetic algorithm, completion time
Abstract
This paper addresses the Hybrid Flow Shop (HFS) scheduling problems to minimize the makespan value. In recent years, much attention is given to heuristic and search techniques. Genetic algorithms (GAs) are also known as efficient heuristic and search techniques. This paper proposes an efficient genetic algorithm for hybrid flow shop scheduling problems. The proposed algorithm is tested by Carlier and Neron’s (2000) benchmark problem from the literature. The computational results indicate that the proposed efficient genetic algorithm approach is effective in terms of reduced total completion time or makespan (Cmax) for HFS problems.
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Journal
International Journal of Computational Intelligence Systems
Volume-Issue
1 - 2
Pages
134 - 147
Publication Date
2008/06
ISSN
1875-6883
DOI
https://doi.org/10.2991/ijcis.2008.1.2.4How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - JOUR
AU  - Cengiz Kahraman
AU  - Orhan Engin
AU  - Ihsan Kaya
AU  - Mustafa Kerim Yilmaz
PY  - 2008
DA  - 2008/06
TI  - An application of effective genetic algorithms for Solving Hybrid Flow Shop Scheduling Problems
JO  - International Journal of Computational Intelligence Systems
SP  - 134
EP  - 147
VL  - 1
IS  - 2
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.2008.1.2.4
DO  - https://doi.org/10.2991/ijcis.2008.1.2.4
ID  - Kahraman2008
ER  -