Critical Issues in Model-Based Surrogate Functions in Estimation of Distribution Algorithms-Reference-Cited by-同舟云学术

Critical Issues in Model-Based Surrogate Functions in Estimation of Distribution Algorithms

Published:2013 Issue: Volume: Page:1-13
ISSN:0302-9743
Container-title:Swarm, Evolutionary, and Memetic Computing
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Author:

Santana Roberto,Mendiburu Alexander,Lozano Jose A.

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-03756-1_1

Reference49 articles.

1. Bielza, C., Li, G., Larranaga, P.: Multi-dimensional classification with Bayesian networks. International Journal of Approximate Reasoning 52(6), 705–727 (2011)

2. Bosman, P.A.: Design and Application of Iterated Density-Estimation Evolutionary Algorithms. PhD thesis, Universiteit Utrecht, Utrecht, The Netherlands (2003)

3. Bosman, P.A., Thierens, D.: Multi-objective optimization with diversity preserving mixture-based iterated density estimation evolutionary algorithms. International Journal of Approximate Reasoning 31(3), 259–289 (2002)

4. Brownlee, A.E.I., Regnier-Coudert, O., McCall, J.A., Massie, S., Stulajter, S.: An application of a GA with Markov network surrogate to feature selection. International Journal of Systems Science 44(11), 2039–2056 (2013)

5. Brownlee, A.E.I., McCall, J., Shakya, S.K.: The Markov Network Fitness Model. In: Shakya, S., Santana, R. (eds.) Markov Networks in Evolutionary Computation, vol. 14, pp. 125–140. Springer (2012)

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