Kenneth A. De Jong, William M. Spears, Diana F. Gordon  Home/Search
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Abstract: Our theoretical understanding of the properties of genetic algorithms (GAs) being used for function optimization (GAFOs) is not as strong as we would like. Traditional schema analysis provides some first order insights, but doesn't capture the non-linear dynamics of the GA search process very well. Markov chain theory has been used primarily for steady state analysis of GAs. In this paper we explore the use of transient Markov chain analysis to model and understand the behavior of finite... (Update)
Context of citations to this paper: More
...than those that do not (e.g. 2, p. 17 18] 6, p. 106] 7] which have been contradicted with empirical evidence in [3] 4] 8] [10]; and many others) 2) the idea that the schema theorem suggests that genetic algorithms offer a near optimal procedure for searching...
.... of Florida Gainesville, FL 32611 352 392 9600 352 392 5438 (FAX) jrees grove.ufl.edu, koehler nervm.nerdc.ufl.edu February 6, 1997 ABSTRACT Theoretical and empirical results give mixed advice for choosing the cardinality for GA representation. Using GA models that...
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14: Adaptation in Natural and Artificial Systems (context) - Holland - 1975
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BibTeX entry: (Update)
K.A. de Jong, W.M. Spears, and D.F. Gordon, Using Markov chains to analyze GAFOs, pp. 115--137 in: L.D. Whitley and M.D. Vose (Eds.), Proc. Foundations of Genetic Algorithms 3, Morgan Kaufmann, 1995. http://citeseer.ist.psu.edu/jong95using.html More
@incollection{ dejong95using,
author = "Kenneth A. {De Jong} and William M. Spears and Diana F. Gordon",
title = "Using Markov Chains to Analyze {GAFO}s",
booktitle = "Foundations of {G}enetic {A}lgorithms 3",
publisher = "Morgan Kaufmann",
address = "San Francisco, CA",
editor = "L. Darrell Whitley and Michael D. Vose",
pages = "115--137",
year = "1995",
url = "citeseer.ist.psu.edu/jong95using.html" }
Citations (may not include all citations):1931 Adaptation in natural and artifi cial systems (context) - Holland - 1975
192 An analysis of the behavior of a class of genetic adaptive s.. (context) - De Jong - 1975
89 The genetic algorithm and the structure of the fitness lands.. (context) - Manderick, de Weger et al. - 1991 DBLP
54 Modeling simple genetic algorithms (context) - Vose - 1992
53 San Mateo (context) - the, Conference et al. - 1994
46 An executable model of a simple genetic algorithm - Whitley - 1992
38 A simulated annealing like convergence theory for the simple.. (context) - Davis, Principe - 1991 DBLP
28 Modelling genetic algorithms with Markov chains (context) - Nix, Vose - 1992
27 Operations Research: Applications and Algorithms (context) - Winston - 1991
26 A Markov chain analysis on a genetic algorithm (context) - Suzuki - 1993
20 Finite Markov chain analysis of genetic algorithms with nich.. - Horn - 1993 ACM DBLP
18 The genetic algorithm fractal (context) - Juliany, Vose - 1994
1 Lawrence Davis (context) - in, Simulated - 1987
1 Simple genetic algorithms and the minimal (context) - Thesis, Computer et al. - 1987
1 GAs are not function optimizers (context) - De Jong - 1992
1 Massively parallel simulated annealing and its relation to e.. (context) - Mathematics, Intelligence et al. - 1994 DBLP
1 Finite Markov chain models of an alternative selection strat.. (context) - Mafoud - 1993
The graph only includes citing articles where the year of publication is known.
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On The State of Evolutionary Computation - De Jong, Spears (1993) (Correct)
Learning Concept Classification Rules Using Genetic Algorithms - De Jong, Spears (1991) (Correct)
An Overview of Evolutionary Computation - Spears, De Jong, Bäck, Fogel, de .. (1993) (Correct)
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