Abstract
This is a summary of the main results presented in the author’s PhD thesis. This thesis was supervised by El-Ghazali Talbi, and defended on 21 June 2005 at the University of Lille (France). It is written in French and is available at http://www.lifl.fr/~basseur/These.pdf. This work deals with the conception of cooperative methods in order to solve multi-objective combinatorial optimization problems. Many cooperation schemes between exact and/or heuristic methods have been proposed in the literature. We propose a classification of such schemes. We propose a new heuristic called adaptive genetic algorithm (AGA), that is designed for an efficient exploration of the search space. We consider several cooperation schemes between AGA and other methods (exact or heuristic). The performance of these schemes are tested on a bi-objective permutation flow-shop scheduling problem, in order to evaluate the interest of each type of cooperation.
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References
Basseur M (2005) Design of cooperative algorithms for multi-objective optimization: Application to the Flow-shop scheduling problem. PhD Thesis, Université de Lille I, Villeveuve d’Ascq France, June 2005
Basseur M, Seynhaeve F, Talbi E-G (2002) Design of multi-objective evolutionary algorithms: application to the flow-shop scheduling problem. In: Congress on Evolutionary Computation CEC’02, Honolulu, Hawaii, USA, May 2002 pp 1151–1156
Basseur M, Seynhaeve F, Talbi E-G (2003) Adaptive mechanisms for multi-objective evolutionary algorithms. In: Congress on Engineering in System Application CESA’03, Lille, France, July 2003 pp 72–86
Basseur M, Lemesre J, Dhaenens C, Talbi E-G (2004) Cooperation between branch and bound and evolutionary approaches to solve a biobjective flow shop problem. In: Workshop on Efficient and Experimental Algorithms (WEA’04), vol 3059. Springer Berlin Heidelberg New York pp 72–86
Basseur M, Seynhaeve F, Talbi E-G (2005a) A cooperative metaheuristic applied to multi-objective flow-shop scheduling problem. In: Nedjah, N., Mourelle, L. (eds) Real-world multi-objective system engineering, chap 6. Nova Science ISBN 1-59454-390-9
Basseur M, Seynhaeve F, Talbi E-G (2005b) Path relinking in pareto multi-objective genetic algorithms. In: Coello Coello CA, Aguirre AH, Zitzler E. (eds) Evolutionary multi-criterion optimization, EMO’2005, vol 3410 of lecture notes in computer science, Guanajuato, Mexico. Springer, Berlin Heidelberg New York, pp 120–134
Deb K (2001) Multi-objective optimization usi ng evolutionary algorithms. Wiley, Chichester
Taillard E (1993) Benchmarks for basic scheduling problems. Eur J Oper Res 64:278–285
Ulungu EL, Teghem J (1995) The two phases method: an efficient procedure to solve bi-objective combinatorial optimization problems. Found Comput Decis Sci 20(2):149–165
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Basseur, M. Design of cooperative algorithms for multi-objective optimization: application to the flow-shop scheduling problem. 4OR 4, 255–258 (2006). https://doi.org/10.1007/s10288-006-0002-8
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DOI: https://doi.org/10.1007/s10288-006-0002-8
Keywords
- Combinatorial optimization
- Multi-objective optimization
- Cooperative methods
- Exact method
- Meta-heuristic
- Flow-shop scheduling