Title :
Controlling diversity of evolutionary algorithms
Author :
Nguyen, D.H.M. ; Wong, K.P.
Author_Institution :
Dept. of Electr. Eng., Hong Kong Polytech. Univ., China
Abstract :
This paper presents a control system based method for adapting the mutation step-size in order to control the diversity of the genome population. Population diversity is controlled so that it decreases exponentially with time in order to facilitate the linear order convergence that evolutionary algorithms are capable of. The paper restricts its attention to the application of unimodal search since linear order convergence of evolutionary algorithms has only been established analytically for unimodal and not for multimodal search. The case of multimodal search is left as an exercise in implementations of sub-population schemes. The paper also highlights the subtle but important difference between setting of EAs parameters and control of EAs performance.
Keywords :
adaptive control; evolutionary computation; adaptive control; diversity control; evolutionary algorithms; feedback control system; genome population; linear order convergence; mutation step-size; population diversity; unimodal search; Adaptive control; Algorithm design and analysis; Automatic control; Bioinformatics; Control systems; Convergence; Evolutionary computation; Genetic mutations; Genomics; Runtime;
Conference_Titel :
Machine Learning and Cybernetics, 2003 International Conference on
Print_ISBN :
0-7803-8131-9
DOI :
10.1109/ICMLC.2003.1259581