Paper Info
Title
Analyzing fitness landscapes for the optimal golomb ruler problem
Abstract
We focus on the Golomb ruler problem, a hard constrained combinatorial optimization problem. Two alternative encodings are considered, one based on the direct representation of solutions, and one based on the use of an auxiliary decoder. The properties of the corresponding fitness landscapes are analyzed. It turns out that the landscape for the direct encoding is highly irregular, causing drift to low-fitness regions. On the contrary, the landscape for the indirect representation is regular, and exhibits comparable fitness-distance correlation to that of the former landscape. These findings are validated in the context of variable neighborhood search.
Year
DOI
Venue
2005
10.1007/978-3-540-31996-2_7
EvoCOP
Keywords
Field
DocType
combinatorial optimization problem,optimal golomb ruler problem,alternative encodings,direct representation,analyzing fitness landscape,comparable fitness-distance correlation,former landscape,indirect representation,golomb ruler problem,corresponding fitness landscape,auxiliary decoder,direct encoding,fitness landscape
Fitness landscape,Evolutionary algorithm,Variable neighborhood search,Golomb ruler,Computer science,Direct representation,Algorithm,Combinatorial optimization,Encoding (memory),Constrained optimization
Conference
Volume
ISSN
ISBN
3448
0302-9743
3-540-25337-8
Citations 
PageRank 
References 
3
0.40
17
Authors
2
Name
Order
Citations
PageRank
Carlos Cotta144136.10
Antonio Fernández280149.47