Ant systems & Local Search Optimization for flexible Job Shop Scheduling Production


  • Noureddine Liouane 1ATSI : Ecole Nationale d’Ingénieurs de Monastir, rue Ibn El Jazzar, 5019 Monastir, Tunisie
  • Ihsen Saad Ecole Centrale de Lille, Cité scientifique Laboratoire d’Automatique, Genie Informatique et Signal BP 48, 59651 Villeneuve d’Ascq Cedex, France
  • Slim Hammadi Ecole Centrale de Lille, Cité scientifique Laboratoire d’Automatique, Genie Informatique et Signal BP 48, 59651 Villeneuve d’Ascq Cedex, France
  • Pierre Borne Ecole Centrale de Lille, Cité scientifique Laboratoire d’Automatique, Genie Informatique et Signal BP 48, 59651 Villeneuve d’Ascq Cedex, France


Flexible production, Ant colony, Tabu search, job shop scheduling, makespan, optimisation


The problem of efficiently scheduling production jobs on several machines is an important consideration when attempting to make effective use of a multimachines system such as a flexible job shop scheduling production system (FJSP). In most of its practical formulations, the FJSP is known to be NP-hard [8][9], so exact solution methods are unfeasible for most problem instances and heuristic approaches must therefore be employed to find good solutions with reasonable search time. In this paper, two closely related approaches to the resolution of the flexible job shop scheduling production system are described. These approaches combine the Ant system optimisation meta-heuristic (AS) with local search methods, including tabu search. The efficiency of the developed method is compared with others.


A. C. F. Alvim, F. Glover, C. C. Ribiero and D. J. Aloise. A hybrid improvement heuristic for the bin packing problem, 2002. Available from:

T. D. Braun, H. J. Siegel, N. Beck, L. L. Bölöni, M. Maheswaran, A. I. Reuther, J. P. Robertson, M. D. Theys, B. Yao, D. Hensgen and R. F. Freund. A comparison of eleven static heuristics formapping a class of independent tasks onto heterogeneous distributed computing systems. Journal of Parallel and Distributed Computing, 61(6):810-837, 2001.

Brandimarte P., Routing and Scheduling in a Flexible Job-Shop by Tabu Search, Annals of Operations Research, vol. 2, pp. 158-183, 1993.

Bilchev, G., Parmee, I.C. : The Ant Colony Metaphor for Searching Continuous Design Spaces. Lecture Notes in Computer Science, 993,pp. 25-39, 1995.

A. L. Corcoran and R. L. Wainwright. A parallel island model genetic algorithm for the multiprocessor scheduling problem. In Selected Areas in Cryptography, pp. 483-487, 1994.

M. Dorigo. Optimization, Learning and Natural Algorithms. PhD thesis, DEI, Polytecnico di Milano, Milan, 1992.

M. Dorigo and T. Stützle. The ant colony optimization metaheuristic: Algorithms, applications, and advances. In Glover, F. and Kochenberger, G., editors, Handbook of Metaheuristics, vol. 57 of International Series in Operations Research and Management Science, pp. 251-285. Kluwer Academic Publishers, 2002.

M. Garey, D. Johnson, R. Sethi. The Complexity of Flow Shop and Job-shop Schedules. Mathematics of Operations Research, vol. 1(2), pp. 117-129, 1976.

M. Garey and D. Johnson. Computers and Intractability: A Guide to the theory of NP-Completeness. Freeman and Company, San Francisco, 1979.

I. Kacem, S. Hammadi and P. Borne. Approach by Localization and Multiobjective Evolutionary Optimization for Flexible Job-shop Scheduling Problems. IEEE Transactions on Systems, Man and Cybernetics, vol. 32(1), pp. 1-13, 2002.

I. Kacem, S. Hammadi and P. Borne. Pareto-optimality Approach for Flexible Job-Shop Scheduling Problems: Hybridization of Evolutionary Algorithms and Fuzzy Logic. Mathematics and Computer in Simulation, vol. 60, pp. 245-276, 2002.

N. Liouane, S. Hammadi and P. Borne. Robust methodology for scheduling production in uncertain environment. IMACS Multi-Conference on Computational Engineering in Systems Applications, CESA'98, Hammamet, 1998.

K. Mesghouni. Application des algorithmes évolutionnistes dans les problèmes d'optimisation en ordonnancement de production. Thèse de Doctorat, Université de Lille1, Lille, 1998.

J. C. Tay and N. B. Ho. GENACE: An Efficient Cultural Algorithm for Solving the Flexible Job- Shop Problem. Proceedings of the IEEE Congress of Evolutionary Computation, pp. 1759-1766, 2004.

A. Thiesen, Design and evaluation of tabu search algorithms for multiprocessor scheduling. Journal of Heuristics, Vol. 4, pp.141-160, 1998.

S. van der Zwaan and C. Marques. Ant colony optimisation for job shop scheduling. In Proceedings of the Third Workshop on Genetic Algorithms and Artificial Life, GAAL 99,1999.



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