Title :
Population fitness probability for effectively terminating the evolution operations of a genetic algorithm
Author :
Heng-Chou Chen ; Chen, Oscal T C
Author_Institution :
Dept. of Electr. Eng., Nat. Chung Cheng Univ., Chia-Yi
Abstract :
A probability associated with the population fitness is used in a genetic algorithm (GA) to terminate the evolution. The theoretically probabilistic derivation of population fitness reveals that the probability is inversely proportional to the individual variation and directly proportional to the evolving error between the average individual and the global optimum of the objective function. Based on the probability, GA switches its operation mode between the genetic operation and the population regeneration. A modified genetic algorithm with a termination strategy is proposed to find the global optima of five objective functions and thus validate the proposed probability of population fitness
Keywords :
genetic algorithms; probability; evolution operation termination; genetic algorithm; genetic operation; objective function; population fitness; population regeneration; probabilistic derivation; probability; Convergence; Genetic algorithms; Genetic mutations; Laboratories; Parameter estimation; Stability; Switches; Upper bound;
Conference_Titel :
Circuits and Systems, 2006. ISCAS 2006. Proceedings. 2006 IEEE International Symposium on
Conference_Location :
Island of Kos
Print_ISBN :
0-7803-9389-9
DOI :
10.1109/ISCAS.2006.1693447
