Abstract
The paper considers the hybrid flow-shop scheduling problem with multiprocessor tasks. Motivated by the computational complexity of the problem, we propose a memetic algorithm for this problem in the paper. We first describe the implementation details of a genetic algorithm, which is used in the memetic algorithm. We then propose a constraint programming based branch-and-bound algorithm to be employed as the local search engine of the memetic algorithm. Next, we present the new memetic algorithm. We lastly explain the computational experiments carried out to evaluate the performance of three algorithms (genetic algorithm, constraint programming based branch-and-bound algorithm, and memetic algorithm) in terms of both the quality of the solutions produced and the efficiency. These results demonstrate that the memetic algorithm produces better quality solutions and that it is very efficient.
Article PDF
Similar content being viewed by others
Avoid common mistakes on your manuscript.
References
Baptiste, Ph., Le Pape, C., Nuijten, W.: Satisfiability tests and time bound adjustments for cumulative scheduling problems. Ann. Oper. Res. 92, 3305–3333 (1999)
Baptiste, Ph., Le Pape, C., Nuijten, W.: Constraint-Based Scheduling, Applying Constraint Programming to Scheduling Problems, vol. 39. International Series in Operations Research and Management Science. Kluwer, Deventer (2001)
Błażewicz, J., Ecker, K.H., Pesch, E., Schmidt, G., Wȩglarz, J.: Scheduling Computer and Manufacturing Processes, 2nd edn. Springer, Berlin (2001)
Carlier, C., Pinson, E.: A practical use of jackson’s preemptive schedule for solving the job-shop problem. Ann. Oper. Res. 26, 269–287 (1990)
Carlier, J., Néron, E.: An exact method for solving the multiprocessor flowshop. RAIRO-RO 34, 1–25 (2000)
Chen, J., Lee, C.-Y.: General multiprocessor task scheduling. Nav. Res. Logist. 46, 57–74 (1999)
Erschler, J., Lopez, P., Thuriot, C.: Raisonnement temporel sous contraintes de ressource et problèmes d’ordonnancement. Rev. Intell. Artif. 5(3), 7–32 (1991)
Goldberg, D.E.: Genetic Algorithms in Search, Optimization and Machine Learning. Addison Wesley, Redwood City (1989)
Goldberg, D.E., Deb, K.: A comparative analysis of selection schemes used in genetic algorithms. In: Rawlins, G.J.E. (ed.) Foundations of Genetic Algorithms, pp. 69–93. Morgan Kaufman, San Mateo (1991)
Gupta, J.N.D.: Two stage hybrid flowshop scheduling problem. J. Oper. Res. Soc. 39(4), 359–364 (1988)
Holland, J.H.: Adaption in Natural and Artificial Systems. University of Michigan Press, Ann Arbor (1975)
Ilog: Ilog Scheduler Reference Manual. Ilog, Gentilly (2004)
Krawczyk, H., Kubale, M.: An approximation algorithm for diagnostic test scheduling in multicomputer systems. IEEE Trans. Comput. 34, 869–872 (1985)
Le Pape, C.: Implementation of resource constraints in ILOG SCHEDULE: a library for the development of constraint-based scheduling systems. Intell. Syst. Eng. 3(2), 55–66 (1994)
Lee, C.-Y., Cai, X.: Scheduling one and two-processor tasks on two parallel processors. IIE Trans. 31, 445–455 (1999)
Lhomme, O.: Consistency techniques for numeric CSPs. In: Thirteenth International Joint Conference on Artificial Intelligence, Chambéry, August 1993
Lopez, P., Erschler, J., Esquirol, P.: Ordonnancement de tâches sous contraintes: une approche énergétique. RAIRO Autom. Prod. Inform. Ind. 26(6), 453–481 (1992)
Moscato, P.: On evolution, search, optimization, genetic algorithms and martial arts: towards memetic algorithms. Technical Report C3P 826, Caltech Concurrent Computation Program, (1989)
Moscato, P.: Memetic algorithms: a short introduction. In: Corne, D., Dorigo, M., Glover, F. (eds.) New Ideas in Optimization, pp. 219–234. McGraw-Hill, New York (1999)
Moscato, P., Cotta, C.: A gentle introduction to memetic algorithms. In: Glover, F., Kochenberger, G.A. (eds.) Handbook of Metaheuristics, pp. 105–144. Kluwer, Deventer (2003)
Néron, E., Baptiste, Ph., Gupta, J.N.D.: Solving hybrid flow shop problem using energetic reasoning and global operations. Omega 29, 501–511 (2001)
Nuijten, W.: Time and resource constrained scheduling: a constraint satisfaction approach. Ph.D. thesis, Eindhoven University of Technology (1994)
Nuijten, W., Aarts, E.H.L.: A computational study of constraint satisfaction for multiple capacitated job-shop scheduling. Eur. J. Oper. Res. 90(2), 269–284 (1996)
Oğuz, C., Ercan, M.F.: A genetic algorithm for hybrid flow-shop scheduling with multiprocessor tasks. J. Sched. 8(4), 323–351 (2005)
Oğuz, C., Ercan, M.F., Cheng, T.C.E., Fung, Y.-F.: Heuristic algorithms for multiprocessor task scheduling in a two-stage hybrid flow-shop. Eur. J. Oper. Res. 149, 390–403 (2003)
Oğuz, C., Zinder, Y., Do, V.H., Janiak, A., Lichtenstein, M.: Hybrid flow-shop scheduling problems with multiprocessor task systems. Eur. J. Oper. Res. 152, 115–131 (2004)
Portmann, M.-C., Vignier, A., Dardilhac, D., Dezalay, D.: Branch and bound crossed with GA to solve hybrid flow shops. Eur. J. Oper. Res. 107, 389–400 (1998)
Serifoğlu, F.S., Ulusoy, G.: Multiprocessor task scheduling in multistage hybrid flow-shops: a genetic algorithm approach. J. Oper. Res. Soc. 55(5), 504–512 (2004)
Vignier, A.: Contribution à la Résolution des Problèmes d’Ordonnancement de type Monogamme, Multimachines Flow-shop hybride. Ph.D. thesis, University of Tours (1997)
Vignier, A., Billaut, J.-C., Proust, C.: Hybrid flowshop scheduling problems: state of the art. Rairo-Rech. Oper.-Oper. Res. 33, 117–183 (1999)
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Jouglet, A., Oğuz, C. & Sevaux, M. Hybrid Flow-Shop: a Memetic Algorithm Using Constraint-Based Scheduling for Efficient Search. J Math Model Algor 8, 271–292 (2009). https://doi.org/10.1007/s10852-008-9101-1
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10852-008-9101-1