An Improved Genetic Algorithm Based on K2(m) Triangulation of Continuous Self-Mapping
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.
Pengcheng Wang, Liqun Ai, Yungang Li, Xiaoming Sang and Jinglong Bu
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