Author:
Iwona Karcz-Duleba
Affiliation:
Wroclaw University of Technology, Poland
Keyword(s):
Phenotypic Evolution, Impatience Operator Without and with Knowledge, Polarization of Population, Bimodal Fitness Function.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Computational Intelligence
;
Evolutionary Computing
;
Genetic Algorithms
;
Hybrid Systems
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Soft Computing
Abstract:
Evolutionary inspired heuristics suffer from a premature convergence at local optima and, consequently, a population
diversity loss. Thus, breaking out of a local optimum trap and crossing saddles between optima in
multimodal and multidimensional search spaces is an important issue in an evolutionary optimization algorithm.
In this paper, an impatience mechanism coupled with a phenotypic model of evolution is studied. This
mechanism diversifies a population and facilitates escaping from a local optima trap. An impatient population
polarizes itself and evolves as a dipole centered around an averaged individual. The operator was modified by
supplying it with an extra knowledge about a currently found optimum. In the case, behavior of a population
is quite different – a significant diversification is observed but the population is not polarized and evolves as
a single cluster. Both mechanisms allow to cross saddle relatively fast for a wide range of parameters of a
bimodal multidimensio
nal fitness function.
(More)