by Tomoyuki Hiroyasu, Mitsunori Miki, Sinya Watanabe
In Proceedings of International Workshop on Emergent Synthesis (IWES’99
http://www.lania.mx/~ccoello/EMOO/hiroyasu99a.ps.gz
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Abstract:
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.
Citations
|
1082
|
Genetic algorithms in search optimization and machine learning
– Goldberg
- 1989
|
|
323
|
Genetic algorithms for multi-objective optimization: Formulation, discussion and generalization
– Fonseca, Fleming
- 1993
|
|
302
|
An Overview of Evolutionary Algorithms in Multiobjecctive
– M, Fleming
- 1995
|
|
246
|
Multiple objective optimization with vector evaluated genetic algorithms
– Schaffer
- 1984
|
|
58
|
An updated survey of evolutionary multiobjective optimization techniques: State of the art and future trends
– Coello
- 1999
|
|
20
|
Topologies, migration rates, and multi-population parallel genetic algorithms
– Cantú-Paz
- 1999
|
|
16
|
Multi-Objective Genetic Algorithms
– Murata, Ishibuchi
- 1995
|
|
7
|
A survey on the parallel genetic algorithms
– Nang, Matsuo
- 1994
|
|
7
|
Sub-population policies for a parallel multiobjective genetic algorithm with applications to wing design
– Quagliarella, Vicini
- 1998
|
|
6
|
Aerodynamic and aeroacoustic optimization of airfoils via a parallel genetic algorithm
– Jones, Crossley, et al.
- 1998
|
|
3
|
Multiple Criteria Decision Making Theory and Application
– Ben-Tai
- 1980
|
|
3
|
Generation of a Set of Pareto-Optimal Solutions by Genetic Algorithms
– Tamaki, Araki
- 1995
|
|
3
|
A study on the effect of multi-parent recombination in real coded genetic algorithms
– unknown authors
- 1998
|
|
2
|
Parallel distributed processing of a parameter-free ga by using hierarchical migration methods
– Sawai, Adachi
- 1999
|
|
1
|
Generation of a Set of Pareto-Optimal Solutions for Multibojective Optimization by Parallel Genetic Algorithms and its Quantitative Evaluation. No. 9, Distributed system symposium
– Hiyane
- 1997
|
