DIVIDED RANGE GENETIC ALGORITHMS IN MULTIOBJECTIVE OPTIMIZATION PROBLEMS

In this paper, Divided Range Genetic Algorithm in Multi objective optimization Problems (DRGA) is proposed. In this method, population of GAs is sorted with respect to the objective function and divided into sub populations. In this model, the Pareto optimum solutions which are close to each other are collected by one sub population. Therefore, by this algorithm, the calculation efficiency is increased, and the neighborhood search can be performed. Through the numerical examples, the followings are made cleared . DRGA is very suitable GA model for parallel processing. DRGA can derive the good solutions compared to the single population model and the distributed model.

[1]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[2]  H. Ishibuchi,et al.  MOGA: multi-objective genetic algorithms , 1995, Proceedings of 1995 IEEE International Conference on Evolutionary Computation.

[3]  Erick Cantú-Paz,et al.  Topologies, Migration Rates, and Multi-Population Parallel Genetic Algorithms , 1999, GECCO.

[4]  A. Vicini,et al.  Sub-population policies for a parallel multiobjective genetic algorithm with applications to wing design , 1998, SMC'98 Conference Proceedings. 1998 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.98CH36218).

[5]  Hidefumi Sawai,et al.  Parallel distributed processing of a parameter-free GA by using hierarchical migration methods , 1999 .

[6]  Gary B. Lamont,et al.  Multiobjective evolutionary algorithm test suites , 1999, SAC '99.

[7]  William A. Crossley,et al.  Aerodynamic and Aeroacoustic Optimization of Rotorcraft Airfoils via a Parallel Genetic Algorithm , 2000 .

[8]  Peter J. Fleming,et al.  Genetic Algorithms for Multiobjective Optimization: FormulationDiscussion and Generalization , 1993, ICGA.

[9]  Peter J. Fleming,et al.  An Overview of Evolutionary Algorithms in Multiobjective Optimization , 1995, Evolutionary Computation.

[10]  Shigeyoshi Tsutsui,et al.  A study on the effect of multi-parent recombination in real coded genetic algorithms , 1998, 1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360).

[11]  Jongho Nang,et al.  A Survey on the Parallel Genetic Algorithms , 1994 .

[12]  Simon French,et al.  Multiple Criteria Decision Making: Theory and Application , 1981 .

[13]  Hisashi Tamaki,et al.  Generation of a Set of Pareto-Optimal Solutions by Genetic Algorithms , 1995 .