Multiobjective Optimization Scheduling Problems by Pareto-optimality in Agro-alimentaryWorkshop
Keywords:
Agro-alimentary workshop, scheduling problems, genetic algorithms, Pareto-optimality, multiobjective optimization, production cost, makespanAbstract
This paper deals with the multiobjective optimization problem of an agroalimentary production workshop. Three criteria are considered in addition to this initial cost of production: the cost of the out-of-date products, the cost of the distribution discount and the makespan, and a new coding is proposed for this type of workshop. The adopted approach consists in generating optimal solutions diversified in the search space of solutions, and to help the decision maker when it cannot give a particular preference to one of the objective functions to make the good decision with respect to the quoted criteria.References
S. Cavalieri, P. Gaiardelli, Hybrid genetic algorithms for a multiple-objective scheduling problem, Journal of Intelligent Manufacturing, Vol.9, pp.361-367, 1998. http://dx.doi.org/10.1023/A:1008935027685
Y. Collette, P. Siarry, Optimisation multiobjectif, Editions Eyrolles, Paris, 2002.
L. Davis, Job shop scheduling with genetic algorithm, Proceedings of the first International Conference on Genetic Algorithms, Lawrence Erlbaum Associates, pp.136-140, 1985.
F. Della Croce, R. Tadei, G. Volta, A genetic algorithm for the job shop problem, Computer and Operations Research, Vol. 22, No 1, pp. 15-24, 1995. http://dx.doi.org/10.1016/0305-0548(93)E0015-L
U. Dorndorf, E. Pesch, Evolution based learning in a job shop environment, Computers and Operations Research, Vol. 22, pp.25-40, 1995. http://dx.doi.org/10.1016/0305-0548(93)E0016-M
E. Gargouri, S. Hammadi, A distributed scheduling for agro-food manufacturing problems, IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, Vol. 33, No 2, 2003. http://dx.doi.org/10.1109/TSMCC.2003.813151
E. Gargouri, S. Hammadi, P.Borne, New constraints of agro-food industry scheduling problem, Acte de IFDICON'2001, Europeen Workshop on Intelligent Forecasting, Diagnostic and Control, 24-28 juin, pp. 73-80, Santorin, 2001.
A. K. Jain, H. A. El Maraghy, Single process plan scheduling with genetic algorithm, Production Planning and Control, Vol.8, No 4, pp.363-376, 1997. http://dx.doi.org/10.1080/095372897235172
I. Kacem, S. Hammadi, P. Borne, Pareto-optimality approach for flexible job-shop scheduling problems: Hybridization of evolutionary algorithms and fuzzy logic, Math. and Computers in Sim., 60, pp. 245-276, 2002. http://dx.doi.org/10.1016/S0378-4754(02)00019-8
K. Mesghouni, Application des algorithmes évolutionnistes dans les problèmes d'optimisation en ordonnancement de la production , PhD Thesis, Université des Sciences et Technologiques de Lille, Lille, 1999.
M. Mori, C. Tseng, Genetic algorithms for multimode resource constrained project scheduling problem, European Journal of Operational Research, Vol.100, No 1, pp.134-141, 1997. http://dx.doi.org/10.1016/S0377-2217(96)00180-4
R. Nakano, T. Yamada, Conventional genetic algorithm for job shop problems, Proceedings of the 4th International Conference on Genetic Algorithms, University of California, pp. 474 -479, 1991.
I. Saad, M. Benrejeb, Optimisation multicritère par Pareto-optimale des problèmes d'ordonnancement en tenant compte du coût de production, Revue Sciences et Technologies de l'Automatique, e-STA, Vol. 3, No. 1, 2006.
M. Sakawa, Genetic algorithms and fuzzy multiobjective optimization, Dordrecht: Kluwer Academic.
E. G. Talbi, Métaheuristiques pour l'optimisation combinatoire multiobjectif, Tutorial, Journées Evolutionnaires Trimestrielles, Paris, 1999.
F. Tangour, S. Hammadi, P. Borne, M. Benrejeb, Ordonnancement dynamique dans un atelier de production agroalimentaire, Séminaire d'Automatique-Industrie, SAI'06, Matmata, 2006.
R. R. Yager, On weighted median aggregation operators in multicriteria decision making, IEEE Trans. on Systems, Man and Cybernetics, 18, pp. 183-190, 1988. http://dx.doi.org/10.1109/21.87068
E. Zitzler, L. Thiele, Multi-objective Evolutionary Algorithms: A Comparative Case Study and the Strength Pareto Approach. IEEE Transactions on Evolutionary Computation, Vol.3, No 4, pp. 257-271, November, 1999. http://dx.doi.org/10.1109/4235.797969
Published
Issue
Section
License
ONLINE OPEN ACCES: Acces to full text of each article and each issue are allowed for free in respect of Attribution-NonCommercial 4.0 International (CC BY-NC 4.0.
You are free to:
-Share: copy and redistribute the material in any medium or format;
-Adapt: remix, transform, and build upon the material.
The licensor cannot revoke these freedoms as long as you follow the license terms.
DISCLAIMER: The author(s) of each article appearing in International Journal of Computers Communications & Control is/are solely responsible for the content thereof; the publication of an article shall not constitute or be deemed to constitute any representation by the Editors or Agora University Press that the data presented therein are original, correct or sufficient to support the conclusions reached or that the experiment design or methodology is adequate.
