Golomb Rulers: A fitness landscape analysis

Author

Tavares, Jorge ; Pereira, Francisco B. ; Costa, Ernesto

Author_Institution

Res. Center Lille-Nord Eur., French Nat. Inst. for Res. in Comput. Sci. & Control (INRIA), Villeneuve d´´Ascq

fYear

2008

fDate

1-6 June 2008

Firstpage

3695

Lastpage

3701

Abstract

Fitness landscape analysis techniques are used to better understand the influence of genetic representations and associated variation operators when solving a combinatorial optimization problem. Several representations for the optimal Golomb ruler problem are examined. Common mutation operators such as bit-flip mutation are employed to generate fitness landscapes to study the genetic representations. Furthermore, additional experiments are made to observe the effects of adding heuristics and local improvements to the encodings.

Keywords

combinatorial mathematics; genetic algorithms; mathematical operators; bit-flip mutation; combinatorial optimization problem; fitness landscape analysis; genetic representations; mutation operators; optimal Golomb ruler problem; variation operators; Codes; Computer science; Crystallography; Error correction; Evolutionary computation; Extraterrestrial measurements; Genetic mutations; Informatics; X-ray detection; X-ray detectors;

fLanguage

English

Publisher

ieee

Conference_Titel

Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on

Conference_Location

Hong Kong

Print_ISBN

978-1-4244-1822-0

Electronic_ISBN

978-1-4244-1823-7

Type

conf

DOI

10.1109/CEC.2008.4631298

Filename

4631298