Title :
A Novel Diversity Induction Method for Bacterial Memetic Algorithm by Hibernation of Individuals
Author_Institution :
Grad. Sch. of Syst. Design, Tokyo Metropolitan Univ., Hino, Japan
Abstract :
Memetic algorithms combine evolutionary algorithms with local search heuristics in order to speed up the evolutionary process. the bacterial memetic algorithm applies the bacterial operators instead of the genetic algorithm´s crossover and mutation operator. in this paper a novel diversity induction method is proposed for bacterial memetic algorithm. Hibernation of some individuals in the population is applied for avoiding premature convergence to local optima. This operation can help in turning back from unpromising region of the search space by previously found solutions represented in hibernated bacteria.
Keywords :
genetic algorithms; microorganisms; search problems; bacterial memetic algorithm; bacterial operators; diversity induction method; evolutionary algorithms; evolutionary process; genetic algorithm crossover operator; genetic algorithm mutation operator; hibernation; local search heuristics; search space; Biological cells; Cloning; Memetics; Microorganisms; Optimization; Sociology; Statistics; bacterial memetic algorithm; diversity; hibernation; memetic algorithm;
Conference_Titel :
Genetic and Evolutionary Computing (ICGEC), 2012 Sixth International Conference on
Conference_Location :
Kitakushu
Print_ISBN :
978-1-4673-2138-9
DOI :
10.1109/ICGEC.2012.25