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Analyzing Fitness Landscapes for the Optimal Golomb Ruler Problem

  • Conference paper
Evolutionary Computation in Combinatorial Optimization (EvoCOP 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3448))

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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.

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Cotta, C., Fernández, A.J. (2005). Analyzing Fitness Landscapes for the Optimal Golomb Ruler Problem. In: Raidl, G.R., Gottlieb, J. (eds) Evolutionary Computation in Combinatorial Optimization. EvoCOP 2005. Lecture Notes in Computer Science, vol 3448. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-31996-2_7

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  • DOI: https://doi.org/10.1007/978-3-540-31996-2_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25337-2

  • Online ISBN: 978-3-540-31996-2

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