A rigorous complexity analysis of the (1+1) evolutionary algorithm for linear functions with Boolean inputs

Author

Droste, Stefan ; Jansen, Thomas ; Wegener, Ingo

Author_Institution

Fachbereich Inf., Dortmund Univ., Germany

fYear

1998

fDate

4-9 May 1998

Firstpage

499

Lastpage

504

Abstract

Evolutionary algorithms (EAs) are heuristic randomized algorithms which, by many impressive experiments, have been proven to behave quite well for optimization problems of various kinds. In this paper, a rigorous complexity analysis of the (1+1) evolutionary algorithm for linear functions with Boolean inputs is given. The analysis is carried out for different mutation rates. The main contribution of the paper is not the result that the expected run time of the (1+1) evolutionary algorithm is at most Θ(n ln n) for linear functions with n variables, but the presentation of methods showing how this result can be proven rigorously

Keywords

Boolean functions; computational complexity; genetic algorithms; heuristic programming; randomised algorithms; (1+1) evolutionary algorithm; Boolean inputs; expected run time; heuristic randomized algorithms; linear functions; mutation rates; optimization problems; rigorous complexity analysis; Algorithm design and analysis; Collaboration; Ear; Electronic switching systems; Evolutionary computation; Genetic algorithms; Genetic mutations; Genetic programming; Heuristic algorithms;

fLanguage

English

Publisher

ieee

Conference_Titel

Evolutionary Computation Proceedings, 1998. IEEE World Congress on Computational Intelligence., The 1998 IEEE International Conference on

Conference_Location

Anchorage, AK

Print_ISBN

0-7803-4869-9

Type

conf

DOI

10.1109/ICEC.1998.700079

Filename

700079