Analyzing fitness landscapes for the optimal golomb ruler problem

Authors:
Carlos Cotta;Antonio J. Fernández
Affiliations:
Dept. Lenguajes y Ciencias de la Computación, ETSI Informática, University of Málaga, Málaga, Spain;Dept. Lenguajes y Ciencias de la Computación, ETSI Informática, University of Málaga, Málaga, Spain
Venue:
EvoCOP'05 Proceedings of the 5th European conference on Evolutionary Computation in Combinatorial Optimization
Year:
2005

Citing 7
Cited 1

Acquistion sequences in PPM communications

IEEE Transactions on Information Theory
Variable neighborhood search

Computers and Operations Research
Fitness Distance Correlation as a Measure of Problem Difficulty for Genetic Algorithms

Proceedings of the 6th International Conference on Genetic Algorithms
Genetic Algorithm Approach to the Search for Golomb Rulers

Proceedings of the 6th International Conference on Genetic Algorithms
GNU Prolog: Beyond Compiling Prolog to C

PADL '00 Proceedings of the Second International Workshop on Practical Aspects of Declarative Languages
A Decoder-Based Evolutionary Algorithm for Constrained Parameter Optimization Problems

PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
A new algorithm for Golomb ruler derivation and proof of the 19 mark ruler

IEEE Transactions on Information Theory

Local Search-based Hybrid Algorithms for Finding Golomb Rulers

Constraints

Quantified Score

Hi-index	0.00

Visualization

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.