An Improved Genetic Algorithm Based on K2(m) Triangulation of Continuous Self-Mapping

Abstract:

Article Preview

In this paper an improved genetic algorithm based on the simplex self-mapping fixed point algorithm is proposed. With this algorithm, the optimal problem of n-dimensional closure function will be transformed as the solution of approximate fixed point problem of n-dimensional standard simplexes by homeomorphism mapping. The genetic operators relying on the integer labels are designed. In this case, whether every individual loading simplex of the population is a completely labeled simplex can be used as an objective convergence criterion. The simulation results demonstrate that the proposed algorithm is valid and effective.

Info:

Periodical:

Advanced Materials Research (Volumes 295-297)

Edited by:

Pengcheng Wang, Liqun Ai, Yungang Li, Xiaoming Sang and Jinglong Bu

Pages:

2515-2520

DOI:

10.4028/www.scientific.net/AMR.295-297.2515

Citation:

J. J. Zhang et al., "An Improved Genetic Algorithm Based on K2(m) Triangulation of Continuous Self-Mapping", Advanced Materials Research, Vols. 295-297, pp. 2515-2520, 2011

Online since:

July 2011

Export:

Price:

$35.00

In order to see related information, you need to Login.

In order to see related information, you need to Login.