Affiliation:
1. Silesian University of Technology
Abstract
In the paper, the problem of achieving Pareto optimal solutions set with application of the elaborated Multi Objectives Immune Algorithm is presented. The Pareto frontier provides a variety of compromise solutions for contradictive criteria to a decision maker. We propose the application of the selection based on the Pareto optimality to maintain solutions with great diversity in an immune memory. Stimulation and suppression mechanisms are used to control the diversity of generated solutions. Computer simulations are done for a job shop scheduling problem.
Publisher
Trans Tech Publications, Ltd.
Reference8 articles.
1. H. Ishibuchi, T. Murata: A Multi–Objective Genetic Local Search Algorithm and Its Application to Flowshop Scheduling, IEEE Transactions on Systems, Man, and Cybernetics- Part C: Applications and Reviews. 28, No. 3 (1998) 392-403.
2. Yiu-Wing Leung, Yuping Wang: Multiobjective Programming Using Uniform Design and Genetic Algorithm, IEEE Transactions on Systems, Man, and Cybernetics- Part C: Applications and Reviews. 30, No. 3 (2000) 293-304.
3. D. Lei: Pareto archive particle swarm optimization for multi-objective fuzzy job shop scheduling problems. Int. J. Adv. Manuf. Technol. 37 (2008) 157-165.
4. M. J. Geiger: On the distribution of Pareto optimal solutions in alternative space - the investigation on multi objective permutation flow shop scheduling problems. Technological and economic development of economy. 12, No. 1 (2006) 23-29.
5. R. Tavakkoli-Moghaddam, A.R. Rahimi-Vahed, A.H. Mirzaei: Solving a multi-objective no-wait flow shop scheduling problem with an immune algorithm. Int. J. Adv. Manuf. Technol. 36 (2008) 969-981.
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