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Abstract: this paper we investigate the e ectiveness of GAs that combine these two methods, more speci - cally, whether the use of a more involved tness function improves the performance of GLS algorithms for random BCSPs. GLS has been recently used in a hybrid GA [3]; at each generation, the o springs produced by the application of genetic operators are improved by means of a local search procedure. Next, we replace the tness function with the tness function from SAW-ing [2] and de ne an adaptive... (Update)
Context of citations to this paper: More
...MID is about five times faster than RIGA. Thus the computational effort of MID can be fairly considered less than the one of RIGA. In [4] it is shown that the performance of RIGA does not improve when the SAW ing method is incorporated in the selection mechanism of the GA:...
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Solving Constraint Satisfaction Problems with Heuristic-based .. - Craenen, Eiben (2000) (Correct)
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0.2: How to Handle Constraints with Evolutionary Algorithms - Craenen, Eiben, Marchiori (2001) (Correct)
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0.4: Recent Work on GLS: a Location Service for an Ad Hoc Network - Guba, Camp (2002) (Correct)
0.4: Solving Binary Constraint Satisfaction Problems.. - Eiben, van.. (1998) (Correct)
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2: Solving Constraint Satisfaction Problems Using A Genetic/Systematic Search Hybri.. (context) - Bowen, Dozier - 1995
BibTeX entry: (Update)
B.G.W. Craenen, A.E Eiben, E. Marchiori, and A. Steenbeek. Combining local search and fitness function adaptation in a GA for solving binary constraint satisfaction problems. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO2000. http://citeseer.ist.psu.edu/craenen00combining.html More
@inproceedings{ marchiori00combining,
author = "A. G. Steenbeek {B. G. W. Craenen, A. E. Eiben, E. Marchiori}",
title = "Combining Local Search and Fitness Function Adaptation in a {GA} for Solving Binary Constraint Satisfaction Problems",
booktitle = "Proceedings of the Genetic and Evolutionary Computation Conference ({GECCO}-2000)",
month = "10-12",
publisher = "Morgan Kaufmann",
address = "Las Vegas, Nevada, USA",
editor = "Darrell Whitley and David Goldberg and Erick Cantu-Paz and Lee Spector and Ian Parmee and Hans-Georg Beyer",
isbn = "1-55860-708-0",
pages = "381",
year = "2000",
url = "citeseer.ist.psu.edu/craenen00combining.html" }
Citations (may not include all citations):17 Solving small and large constraint satisfaction problems usi.. (context) - Dozier, Bowen et al. - 1994
6 Genetic local search algorithm for random binary constraint .. - Marchiori, Steenbeek - 2000
5 SAW-ing EAs: Adapting the tness function for solving constra.. (context) - Eiben, van Hemert - 1999
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An Experimental Comparison of SAWing EAs for a new Class of.. - Craenen, Eiben (2002) (Correct)
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