Title :
Benefits of a Periodic Selection Event in Evolutionary Strategy Algorithms
Author :
Nicholson, John ; White, M.
Author_Institution :
Ph. D. student in the Department of Electrical and Computer Engineering, North Carolina State University, Raleigh, NC 27695-7911, USA. (email: jwnichol@ncsu.edu)
Abstract :
We compare common, fixed population size evolutionary strategies with a strategy incorporating a growing population size and intermittent selection events. In the latter strategy, the population size grows geometrically and selection free every generation. After a fixed number of generations, a selection event occurs which kills many of the individuals in the population and reduces the population size back to an initial value. The quality of solutions and speed of this algorithm are compared using four real-valued problem domains, to common evolutionary strategy algorithms based on (mu, lambda) and (mu+lambda), with promising results.
Keywords :
evolutionary computation; evolutionary strategy algorithms; fixed population size evolutionary strategies; periodic selection event; population size; Bioinformatics; Computational modeling; Contracts; Genetic mutations; Genomics; Insects; Random variables; Sampling methods; Size control;
Conference_Titel :
Evolutionary Computation, 2006. CEC 2006. IEEE Congress on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-9487-9
DOI :
10.1109/CEC.2006.1688299