Title :
A dynamic mutation genetic algorithm
Author :
Hong, Tzung-Pei ; Wang, Hong-Shung
Author_Institution :
Dept. of Inf. Manage, Kaohsiung Polytech. Inst., Taiwan
Abstract :
Conventional genetic algorithms use only one mutation operator to generate the next generation. Determining which mutation operator should be used is quite difficult and is usually done by trial-and-error. In this paper, a new genetic algorithm, the dynamic mutation genetic algorithm (DMGA), is proposed to solve the problem. The dynamic mutation genetic algorithm uses more than one mutation operator to generate the next generation. The mutation ratio of each operator changes along with the evaluation results from the respective offspring in the next generation. We thus expect that really good operators will have an increased effect on the genetic process
Keywords :
genetic algorithms; dynamic mutation genetic algorithm; genetic process; mutation ratio; Automatic control; Electrical capacitance tomography; Fuzzy logic; Genetic algorithms; Genetic mutations; Information management; Machine learning;
Conference_Titel :
Systems, Man, and Cybernetics, 1996., IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-3280-6
DOI :
10.1109/ICSMC.1996.565436