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JRM Vol.10 No.4 pp. 315-325
doi: 10.20965/jrm.1998.p0315
(1998)

Paper:

Set Representation Using Schemata and its Constructing Method from Population in GA

Naohiko Hanajima, Mitsuhisa Yamashita and Hiromitsu Hikita

Dept. of Mechanical Systems Engineering, Muroran Institute of Technology, 27-1, Mizumoto-cho, Muroran, Hokkaido 050-8585, Japan

Received:
April 1, 1998
Accepted:
June 5, 1998
Published:
August 20, 1998
Keywords:
Genetic algorithms, Sets of solution, Schema representation, Schema set construction, Set representation
Abstract

When we invoke genetic algorithms (GAs), we retrieve enormous numbers of individuals. If we can construct, simply, a set having some sense from individuals, it would make engineering applications easier. Schemata in GAs is a simple forms representing such a set. We define modified schemata where instances of a schema represent a continuous region assuming that the GA phenotype is real vector space. We induce expected and maximum numbers of schemata required to represent any continuous region. We show ways to construct a schema set from individuals in GA, constructing a Pareto optimum set on multiobjective optimization theory.

Cite this article as:
Naohiko Hanajima, Mitsuhisa Yamashita, and Hiromitsu Hikita, “Set Representation Using Schemata and its Constructing Method from Population in GA,” J. Robot. Mechatron., Vol.10, No.4, pp. 315-325, 1998.
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