DocumentCode :
412720
Title :
Population size vs. runtime of a simple EA
Author :
Witt, Carsten
Author_Institution :
FB Informatik, Dortmund Univ., Germany
Volume :
3
fYear :
2003
fDate :
8-12 Dec. 2003
Firstpage :
1996
Abstract :
Evolutionary algorithms (EA) finds numerous applications, and practical knowledge on EAs is immense. In practice, sophisticated population-based EAs employing selection, mutation and crossover are applied. In contrast, theoretical analysis of EAs often concentrates on very simple algorithms like the (1+1) EA, where population size equals 1. In this paper, the question is addressed whether the use of a population by itself can be advantageous. A population-based EA does neither make use of crossover nor any diversity-maintaining operator is investigated on an example function. It is shown that an increase of the population size by polynomial factor decreases the expected runtime exponential to polynomial. Thereby, the so far best known gap is improved from superpolynomial to exponential. Moreover, it is proved that the stated runtime bounds occur with a probability exponentially close to one. Finally, a second example function is presented, where opposite results hold.
Keywords :
evolutionary computation; diversity-maintaining operator; evolutionary algorithms; population-based EA; runtime exponential; runtime polynomial; theoretical analysis; Algorithm design and analysis; Evolutionary computation; Genetic algorithms; Genetic mutations; Helium; Polynomials; Roads; Runtime;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation, 2003. CEC '03. The 2003 Congress on
Print_ISBN :
0-7803-7804-0
Type :
conf
DOI :
10.1109/CEC.2003.1299918
Filename :
1299918
Link To Document :
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