The lightweight genetic search algorithm: an efficient genetic algorithm for small search range problems

Author

Lin, Chun-Hung ; WU, JA-LING

Author_Institution

Dept. of Comput. Sci. & Inf. Eng., Nat. Taiwan Univ., Taipei, Taiwan

fYear

1998

fDate

4-9 May 1998

Firstpage

615

Lastpage

620

Abstract

In this paper, the effectiveness of the genetic operations of the common genetic algorithms, such as crossover and mutation, are analyzed for small search range situations. As expected, the thus-obtained efficiency/performance of the genetic operations is quite different from that of their large search range counterparts. To fill this gap, a lightweight genetic search algorithm is presented to provide an efficient way for generating near-optimal solutions for these kinds of applications

Keywords

computational complexity; genetic algorithms; mathematical operators; search problems; crossover; efficiency; genetic operation effectiveness; lightweight genetic search algorithm; mutation; near-optimal solutions; performance; small search range problems; Algorithm design and analysis; Computational complexity; Genetic algorithms; Genetic mutations; Motion estimation; Multimedia communication; Productivity; Strain control; Time factors; Video coding;

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.1998.700099

Filename

700099