论文信息 - The performance of the gene expression messy genetic algorithm on real test functions

The performance of the gene expression messy genetic algorithm on real test functions

The paper reports the performance of an experimental version of the recently introduced gene expression messy genetic algorithm (GEMGA) (H. Kargupta, 1996) for different classes of real test problems. A more recent version of GEMGA can be found elsewhere. The GEMGA has a strong computational and biological foundation. It emphasizes the role of gene expression in evolution and it searches for relations among genes using transcription like operators. The particular version of GEMGA used in this work is an O(A/sup k/(l+k)) sample complexity algorithm for the class of order-k delineable problems (H. Kargupta, 1995) (problems that can be solved by considering no higher than order-k relations).

Hillol Kargupta | H. Kargupta

[1] K. Deb. Binary and floating-point function optimization using messy genetic algorithms , 1991 .

[2] Kenneth Alan De Jong,et al. An analysis of the behavior of a class of genetic adaptive systems. , 1975 .

[3] Kalyanmoy Deb,et al. Messy Genetic Algorithms: Motivation, Analysis, and First Results , 1989, Complex Syst..

[4] Hillol Kargupta,et al. The Gene Expression Messy Genetic Algorithm , 1996, Proceedings of IEEE International Conference on Evolutionary Computation.