Progress properties and fitness bounds for geometric semantic search operators-Reference-Cited by-同舟云学术

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Progress properties and fitness bounds for geometric semantic search operators

Published:2015-10-22 Issue:1 Volume:17 Page:5-23
ISSN:1389-2576
Container-title:Genetic Programming and Evolvable Machines
language:en
Short-container-title:Genet Program Evolvable Mach

Author:

Pawlak Tomasz P.^ORCID,Krawiec Krzysztof

Funder

Narodowe Centrum Nauki (PL)

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Hardware and Architecture,Theoretical Computer Science,Software

Link

http://link.springer.com/content/pdf/10.1007/s10710-015-9252-6.pdf

Reference33 articles.

1. L. Beadle, C. Johnson, Semantically driven crossover in genetic programming, in Proceedings of the IEEE World Congress on Computational Intelligence, ed. by J. Wang (IEEE Computational Intelligence Society, IEEE Press, Hong Kong, 2008), pp. 111–116. doi: 10.1109/CEC.2008.4630784 , http://results.ref.ac.uk/Submissions/Output/1423275

2. L. Beadle, C.G. Johnson, Semantic analysis of program initialisation in genetic programming. Genet. Program. Evolv. Mach. 10(3), 307–337 (2009). doi: 10.1007/s10710-009-9082-5 . http://www.springerlink.com/content/yn5p45723l6tr487

3. L. Beadle, C.G. Johnson, Semantically driven mutation in genetic programming. in 2009 IEEE Congress on Evolutionary Computation, ed. by A. Tyrrell, (IEEE Computational Intelligence Society, IEEE Press, Trondheim, Norway, 2009), pp. 1336–1342. doi: 10.1109/CEC.2009.4983099

4. M. Castelli, L. Vanneschi, S. Silva, Prediction of high performance concrete strength using genetic programming with geometric semantic genetic operators. Exp. Syst. Appl. 40(17), 6856–6862 (2013). doi: 10.1016/j.eswa.2013.06.037 . http://www.sciencedirect.com/science/article/pii/S0957417413004326

5. G. Durrett, F. Neumann, U.M. O’Reilly, Computational complexity analysis of simple genetic programming on two problems modeling isolated program semantics. in Foundations of Genetic Algorithms, ed. by H.G. Beyer, W.B. Langdon (ACM, Schwarzenberg, Austria, 2011), pp. 69–80. doi: 10.1145/1967654.1967661

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5. Genetic Programming With Mixed-Integer Linear Programming-Based Library Search;IEEE Transactions on Evolutionary Computation;2018-10

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