The week's pick
Reseach Article
Genetic Algorithm Tuning Applied to the Open Shop Scheduling Problem
| International Journal of Applied Information Systems |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 11 - Number 3 |
| Year of Publication: 2016 |
| Authors: Chaouqi Mohsine, Benhra Jamal, My Ali El Oualidi |
10.5120/ijais2016451588
|
Chaouqi Mohsine, Benhra Jamal, My Ali El Oualidi . Genetic Algorithm Tuning Applied to the Open Shop Scheduling Problem. International Journal of Applied Information Systems. 11, 3 ( Aug 2016), 21-25. DOI=10.5120/ijais2016451588
Abstract
The present paper deals with the open-shop scheduling problem using a manual tuning of a genetic algorithm’s parameters. A comparison has been performed between Taillard’s Benchmarks for 60 instances, 2 dispatching rules and 198 variants from the GA algorithm obtained by changing the population size, the generation’s number, the crossover probability, and the mutation probability. Interesting results were obtained leading to some conclusions for the best choice of the parameters.
References
- M. L. Pinedo, Scheduling, vol. 1. Boston, MA: Springer US, 2012.
- F. Werner, “Genetic algorithms for shop scheduling problems: A survey,” Preprint, 2011.
- M. Chaouqi and J. Benhra, “Recuit simulé hybride pour un ordonnancement conjoint de la production et de la maintenance dans un atelier job-shop,” Int. Work. Theory Appl. Logist. Transp. TALT15, 2015.
- P. S. J. Dréo, A. Pétrowski, E. Taillard, Metaheuristics for Hard Optimization, vol. 53, no. 9. Berlin/Heidelberg: Springer-Verlag, 2006.
- M. Andresen, H. Bräsel, M. Mörig, J. Tusch, F. Werner, and P. Willenius, “Simulated annealing and genetic algorithms for minimizing mean flow time in an open shop,” Math. Comput. Model., vol. 48, no. 7–8, pp. 1279–1293, Oct. 2008.
- R. L. Graham, E. L. Lawler, J. K. Lenstra, and A. H. G. Rinnooy Kan, “Optimization and approximation in deterministic sequencing and scheduling : a survey,” 1979.
- C.-F. Liaw, “A hybrid genetic algorithm for the open shop scheduling problem,” Eur. J. Oper. Res., vol. 124, no. 1, pp. 28–42, Jul. 2000.
- Taillard E., “Benchmarks for basic scheduling problems,” Eur. J. Oper. Res., vol. 64, pp. 1–17, 1993.
- P. Brucker, J. Hurink, B. Jurisch, and B. Wöstmann, “A branch & bound algorithm for the open-shop problem,” Discret. Appl. Math., vol. 76, no. 1–3, pp. 43–59, Jun. 1997.
- H. Fang and P. Ross, “A Promising Hybrid GA/Heuristic Approach for Open-Shop Scheduling Problems In Proceedings of the 11th European Conference on Arti cial Intelligence, John Wiley and Sons, 1994, pages 590{594.,” no. 699, 1994.
- S. Khuri and S. R. Miryala, “Genetic Algorithms for Solving Open Shop Scheduling Problems,” in Proceedings of the 9th Portuguese Conference on Artificial Intelligence: Progress in Artificial Intelligence (EPIA ’99), 1999, pp. 357–368.
- C. Prins, “Competitive genetic algorithms for the open-shop problem,” Math. Methods Oper. Res., vol. 52, no. 3, pp. 389–411, 2000.
- P. Senthilkumar and P. Shahabudeen, “GA based heuristic for the open job shop scheduling problem,” Int. J. Adv. Manuf. Technol., vol. 30, no. 3–4, pp. 297–301, 2006.
- M. Chaouqi, J. Benhra, and A. Zakari, “Agile Approach for Joint Scheduling of Production and Maintenance in Flow Shop,” Int. J. Comput. Appl., vol. 59, no. 11, pp. 29–36, Dec. 2012.
- D. Bai, Z.-H. Zhang, and Q. Zhang, “Flexible open shop scheduling problem to minimize makespan,” Comput. Oper. Res., vol. 67, pp. 207–215, Mar. 2016.
- B. Naderi and M. Zandieh, “Modeling and scheduling no-wait open shop problems,” Int. J. Prod. Econ., vol. 158, pp. 256–266, Dec. 2014.
- G. SHl, “A genetic algorithm applied to a classic job-shop scheduling problem,” Int. J. Syst. Sci., vol. 28, no. 1, pp. 25–32, Apr. 2007.
Index Terms
Keywords