Enhancing the Efficiency of the ECGA

In this paper we show preliminary results of two efficiency enhancements proposed for Extended Compact Genetic Algorithm. First, a model building enhancement was used to reduce the complexity of the process from O(n3) to O(n2), speeding up the algorithm by 1000 times on a 4096 bits problem. Then, a local-search hybridization was used to reduce the population size by at least 32 times, reducing the memory and running time required by the algorithm. These results are the first steps toward a competent and efficient Genetic Algorithm.

[1]  David E. Goldberg,et al.  The compact genetic algorithm , 1999, IEEE Trans. Evol. Comput..

[2]  Xavier Llorà,et al.  Toward routine billion-variable optimization using genetic algorithms: Short Communication , 2007 .

[3]  Dirk Thierens,et al.  Mixing in Genetic Algorithms , 1993, ICGA.

[4]  David E. Goldberg,et al.  Efficiency Enhancement of Probabilistic Model Building Genetic Algorithms , 2004, ArXiv.

[5]  J. A. Lozano,et al.  Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation , 2001 .

[6]  David E. Goldberg,et al.  Designing efficient and accurate parallel genetic algorithms (parallel algorithms) , 1999 .

[7]  David E. Goldberg,et al.  Combining competent crossover and mutation operators: a probabilistic model building approach , 2005, GECCO '05.

[8]  Martin Pelikan,et al.  Hierarchical Bayesian optimization algorithm: toward a new generation of evolutionary algorithms , 2010, SICE 2003 Annual Conference (IEEE Cat. No.03TH8734).

[9]  David E. Goldberg,et al.  Conquering hierarchical difficulty by explicit chunking: substructural chromosome compression , 2006, GECCO '06.

[10]  Xavier Llorà,et al.  Toward routine billion-variable optimization using genetic algorithms , 2007, Complex..

[11]  David E. Goldberg,et al.  Sporadic model building for efficiency enhancement of hierarchical BOA , 2006, GECCO '06.

[12]  Goldberg,et al.  Genetic algorithms , 1993, Robust Control Systems with Genetic Algorithms.

[13]  Riccardo Poli,et al.  Genetic and Evolutionary Computation – GECCO 2004 , 2004, Lecture Notes in Computer Science.

[14]  G. Harik Linkage Learning via Probabilistic Modeling in the ECGA , 1999 .

[15]  David E. Goldberg,et al.  Designing Efficient Genetic and Evolutionary Algorithm Hybrids , 2005 .

[16]  Franz Rothlauf,et al.  Evaluation-Relaxation Schemes for Genetic and Evolutionary Algorithms , 2004 .

[17]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[18]  Xavier Llorà,et al.  Towards billion-bit optimization via a parallel estimation of distribution algorithm , 2007, GECCO '07.

[19]  D. Goldberg,et al.  A matrix approach for finding extrema: problems with modularity, hierarchy, and overlap , 2006 .

[20]  David E. Goldberg,et al.  Optimizing Global-Local Search Hybrids , 1999, GECCO.

[21]  D. Goldberg,et al.  BOA: the Bayesian optimization algorithm , 1999 .

[22]  David E. Goldberg,et al.  Let's Get Ready to Rumble: Crossover Versus Mutation Head to Head , 2004, GECCO.

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

[24]  Erick Cantú-Paz Designing Efficient and Accurate Parallel Genetic Algorithms , 1999 .

[25]  Fernando G. Lobo,et al.  Extended Compact Genetic Algorithm in C , 1999 .

[26]  David E. Goldberg,et al.  The Design of Innovation: Lessons from and for Competent Genetic Algorithms , 2002 .