Remapping Hyperspace During Genetic Search: Canonical Delta Folding

Delta coding, an iterative strategy for genetic search, has been empirically shown to improve genetic search performance for some optimization problems. However, detailed analyses reveal that the remapping of hyperspace produced by delta coding is rudimentary. The underlying mechanisms of delta coding are examined and a more robust remapping method is introduced. Canonical delta folding provides a canonical ordering of the strings in the search space and then employs a powerful folding mechanism for remapping hyperspace. The behavior of canonical delta folding for remapping deceptive functions is examined using a set of exact equations for modeling the computational behavior of a simple genetic algorithm.

[1]  L. Darrell Whitley,et al.  Fundamental Principles of Deception in Genetic Search , 1990, FOGA.

[2]  J. David Schaffer,et al.  Proceedings of the third international conference on Genetic algorithms , 1989 .

[3]  Larry J. Eshelman,et al.  The CHC Adaptive Search Algorithm: How to Have Safe Search When Engaging in Nontraditional Genetic Recombination , 1990, FOGA.

[4]  L. Darrell Whitley,et al.  GENITOR II: a distributed genetic algorithm , 1990, J. Exp. Theor. Artif. Intell..

[5]  Michael D. Vose,et al.  Isomorphisms of Genetic Algorithms , 1993, Artif. Intell..

[6]  Kalmanje Krishnakumar,et al.  Micro-Genetic Algorithms For Stationary And Non-Stationary Function Optimization , 1990, Other Conferences.

[7]  Gunar E. Liepins,et al.  Punctuated Equilibria in Genetic Search , 1991, Complex Syst..

[8]  L. Darrell Whitley,et al.  Delta Coding: An Iterative Search Strategy for Genetic Algorithms , 1991, ICGA.

[9]  David E. Goldberg,et al.  Sizing Populations for Serial and Parallel Genetic Algorithms , 1989, ICGA.

[10]  L. Darrell Whitley,et al.  Optimization Using Distributed Genetic Algorithms , 1990, PPSN.

[11]  Lashon B. Booker,et al.  Proceedings of the fourth international conference on Genetic algorithms , 1991 .

[12]  C. G. Shaefer.  ARGOT strategy: adaptive respresentation genetic optimizer technique , 1987 .

[13]  L. Darrell Whitley,et al.  The GENITOR Algorithm and Selection Pressure: Why Rank-Based Allocation of Reproductive Trials is Best , 1989, ICGA.

[14]  GUNAR E. LIEPINS,et al.  Representational issues in genetic optimization , 1990, J. Exp. Theor. Artif. Intell..