Volume 1, Issue 2, May 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
Received 4 September 2007, Revised 4 December 2007, Available Online 1 May 2008.
- DOI
- 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.
- Copyright
- © 2008, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - JOUR AU - Cengiz Kahraman AU - Orhan Engin AU - Ihsan Kaya AU - Mustafa Kerim Yilmaz PY - 2008 DA - 2008/05/01 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 - 10.2991/ijcis.2008.1.2.4 ID - Kahraman2008 ER -