Hidden Genes Genetic Optimization for Variable-Size Design Space Problems

被引：20

作者：

Abdelkhalik, Ossama ^{[1
]}

机构：

[1] Michigan Tech Univ, Mech Engn Engn Mech Dept, Houghton, MI 49931 USA

来源：

JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS | 2013年 / 156卷 / 02期

关键词：

Global optimization; Variable length genetic algorithms; Hidden genes genetic algorithms; PIXEL CLASSIFICATION; GLOBAL OPTIMIZATION; COLONY; ALGORITHMS;

D O I：

10.1007/s10957-012-0122-6

中图分类号：

C93 [管理学]; O22 [运筹学];

学科分类号：

070105 ; 12 ; 1201 ; 1202 ; 120202 ;

摘要：

This paper introduces the biologically inspired concept of hidden genes genetic algorithms; they search for optimal solutions to global optimization problems of multimodal objective functions with a variable number of design variables. A fixed chromosome length is assumed for all solutions in the population. Each chromosome is divided into effective and ineffective segments. The effective segment includes the design variables for that solution. The ineffective segment includes only hidden genes. Hidden genes are excluded in objective function evaluations. The effect of the hidden genes on the convergence of the genetic algorithm is studied. Two test cases are presented.

引用

页码：450 / 468

页数：19

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