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International Workshop on Foundations of Genetic Algorithms

FOGA 2005: Foundations of Genetic Algorithms pp 300–314Cite as

The Deceptive Degree of the Objective Function

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3469))

Abstract

In this paper we present a novel quantitative measure metric for the “degree of deception” of a problem. We present a new definition for the deceptive degree of a function. We investigate the relationship between the best solution and the monomial coefficients of a function, and we give theorems that show the usefulness of the new definition. The new definition can be applied in three ways: it gives a quantitative measure of deception, it simplifies the evaluation of the GA difficulty, and it gives a relationship between the deceptive degree and the polynomial degree. Furthermore we use the deceptive degree of a function to discuss Goldberg’s Minimal Deceptive Problem and derive the same result as Goldberg did. Finally, we make experiments with a class of fitness functions to verify the relation between the canonical GA difficulty and the deceptive degree of a function for this class of functions.

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Author information

Authors and Affiliations

  1. Electronic Technique Institute, Zhengzhou Information Engineering University, 450004, Zhengzhou, China

    Yun-qiang Li

Authors
  1. Yun-qiang Li
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Editor information

Editors and Affiliations

  1. Dept. of Computer Science, University of Montana, 59812, Missoula, Montana, USA

    Alden H. Wright

  2. Computer Science Department, University of Tennessee, 37996, Knoxville, TN, USA

    Michael D. Vose

  3. Computer Science Department, George Mason University, 4400 University Drive, 22030, Fairfax, VA, USA

    Kenneth A. De Jong

  4. School of Computer Science and Engineering, The University of Aizu, 965-8580, Aizu-Wakamatsu City, Fukushima Prefecture, Japan

    Lothar M. Schmitt

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© 2005 Springer-Verlag Berlin Heidelberg

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Li, Yq. (2005). The Deceptive Degree of the Objective Function. In: Wright, A.H., Vose, M.D., De Jong, K.A., Schmitt, L.M. (eds) Foundations of Genetic Algorithms. FOGA 2005. Lecture Notes in Computer Science, vol 3469. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11513575_16

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  • DOI: https://doi.org/10.1007/11513575_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-27237-3

  • Online ISBN: 978-3-540-32035-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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