Ordering genetic algorithm genomes with reconstructability analysis

The building block hypothesis implies that genetic algorithm (GA) effectiveness is influenced by the relative location of epistatic genes on the chromosome. We demonstrate this effect in four experiments, where chromosomes with adjacent epistatic genes provide improved results over chromosomes with separated epistatic genes. We also show that information-theoretic reconstructability analysis can be used to decide on optimal gene ordering.

[1]  M. Zwick.  Wholes and Parts in General Systems Methodology , 2001 .

[2]  M. Zwick,et al.  Reconstructability Analysis Detection of Optimal Gene Order in Genetic Algorithms , 2004 .

[3]  Christopher J. Thornton,et al.  The building block fallacy , 1997 .

[4]  W. Ashby,et al.  Constraint analysis of many-dimensional relations. , 1965, Progress in biocybernetics.

[5]  M. Barbara,et al.  The discovery of characterization of transposable elements : the collected papers of Barbara McClintock , 1987 .

[6]  George J. Klir,et al.  Third w. ross ashby memorial lecture 1986: Reconstructability analysis: An offspring of ashby's constraint analysis , 1986 .

[7]  Ralph R. Martin,et al.  Reducing Epistasis in Combinatorial Problems by Expansive Coding , 1993, ICGA.

[8]  Klaus Krippendorff,et al.  Information Theory: Structural Models for Qualitative Data. , 1988 .

[9]  G. Wagner,et al.  Population dependent Fourier decomposition of fitness landscapes over recombination spaces: Evolvability of complex characters , 2000, Bulletin of mathematical biology.

[10]  Melanie Mitchell,et al.  An introduction to genetic algorithms , 1996 .

[11]  Ashby Wr,et al.  Constraint analysis of many-dimensional relations. , 1965 .

[12]  Martin Zwick,et al.  A SOFTWARE ARCHITECTURE FOR RECONSTRUCTABILITY ANALYSIS , 2004 .

[13]  Stephen Shervais,et al.  Adaptive Critic Design of Control Policies for A Multi-Echelon Inventory System , 2000 .

[14]  Peter Burke,et al.  Log-linear models , 1980 .

[15]  A. Griffiths.  Introduction to Genetic Analysis , 1976 .

[16]  Martin Zwick,et al.  Ordering genetic algorithm genomes with reconstructability analysis: discrete models , 2005, 2005 IEEE International Conference on Systems, Man and Cybernetics.

[17]  Konstantinos G. Margaritis,et al.  An experimental study of benchmarking functions for genetic algorithms , 2000, Smc 2000 conference proceedings. 2000 ieee international conference on systems, man and cybernetics. 'cybernetics evolving to systems, humans, organizations, and their complex interactions' (cat. no.0.

[18]  Bush Jones,et al.  Architecture of systems problem solving , 1986, Journal of the American Society for Information Science.

[19]  P. Holland,et al.  Discrete Multivariate Analysis. , 1976 .

[20]  Nina V. Fedoroff,et al.  The discovery and characterization of transposable elements. The collected papers of Barbara McClintock New York: Garland Publishing, Inc. (1987). 636 pp. $75.00 , 1988, Cell.

[21]  Stuart A. Kauffman,et al.  ORIGINS OF ORDER , 2019, Origins of Order.

[22]  Martin Zwick,et al.  An overview of reconstructability analysis , 2004 .

[23]  Kalyanmoy Deb,et al.  RapidAccurate Optimization of Difficult Problems Using Fast Messy Genetic Algorithms , 1993, ICGA.

[24]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[25]  Anabela Simões,et al.  Transposition: A Biological-Inspired Mechanism to Use with Genetic Algorithms , 1999, ICANNGA.