Title :
Convergence and calculation efficiency analysis of abstract model of nonlinear genetic algorithm based on function group
Author :
Zhi-Hua, Cui ; Jian-Chao, Zeng ; Yu-Bin, Xu
Author_Institution :
Div. of Syst. & Simulation & Comput. Application, Taiyuan Heavy Machinery Inst., China
Abstract :
Through mechanism analysis of genetic algorithm (GAs), every genetic operator of SGA and their combination action can be considered as linear transformations to the corresponding individuals. By modifying the traditional genetic operators, the nonlinear genetic algorithm (NGA) is introduced. In this paper, abstract model of NGA based on function group is discussed in which every function is selected with some probability, and if the function group is correctly selected, then the algorithm can be convergent to global optimal within every given generation number. With this technique the premature convergence and calculation efficiency may be solved.
Keywords :
convergence of numerical methods; genetic algorithms; mathematical operators; neural nets; probability; abstract model; calculation efficiency analysis; function group; generation number; genetic operators; linear transformations; mechanism analysis; nonlinear genetic algorithm; premature convergence; selection principles; Algorithm design and analysis; Analytical models; Computational modeling; Computer applications; Computer simulation; Convergence; Genetic algorithms; Genetic mutations; Machinery; Random variables;
Conference_Titel :
Systems, Man and Cybernetics, 2003. IEEE International Conference on
Print_ISBN :
0-7803-7952-7
DOI :
10.1109/ICSMC.2003.1245718