Pairwise and problem-specific distance metrics in the linkage tree genetic algorithm

The linkage tree genetic algorithm (LTGA) identifies linkages between problem variables using an agglomerative hierarchical clustering algorithm and linkage trees. This enables LTGA to solve many decomposable problems that are difficult with more conventional genetic algorithms. The goal of this paper is two-fold: (1) Present a thorough empirical evaluation of LTGA on a large set of problem instances of additively decomposable problems and (2) speed up the clustering algorithm used to build the linkage trees in LTGA by using a pairwise and a problem-specific metric.

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

[2]  David E. Goldberg,et al.  Learning Linkage , 1996, FOGA.

[3]  Stuart A. Kauffman,et al.  The origins of order , 1993 .

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

[5]  Martin Pelikan,et al.  Intelligent bias of network structures in the hierarchical BOA , 2009, GECCO.

[6]  Kalyanmoy Deb,et al.  Analyzing Deception in Trap Functions , 1992, FOGA.

[7]  Dirk Thierens,et al.  Scalability Problems of Simple Genetic Algorithms , 1999, Evolutionary Computation.

[8]  David E. Goldberg,et al.  Scalability of the Bayesian optimization algorithm , 2002, Int. J. Approx. Reason..

[9]  Martin Pelikan.  NK landscapes, problem difficulty, and hybrid evolutionary algorithms , 2010, GECCO '10.

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

[11]  David E. Goldberg,et al.  Population sizing for entropy-based model building in discrete estimation of distribution algorithms , 2007, GECCO '07.

[12]  David H. Ackley,et al.  An empirical study of bit vector function optimization , 1987 .

[13]  Dirk Thierens,et al.  The Linkage Tree Genetic Algorithm , 2010, PPSN.

[14]  Martin Pelikan,et al.  Enhancing Efficiency of Hierarchical BOA Via Distance-Based Model Restrictions , 2008, PPSN.

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

[16]  David E. Goldberg,et al.  Bayesian Optimization Algorithm, Population Sizing, and Time to Convergence , 2000, GECCO.

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

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