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Classes of problems in the black box scenario

Published: 08 July 2006 Publication History

Abstract

The no-free-lunch theorems (NFLTs) do not consider explicitly the structure of problems. In [1] we gave a formal definition of structure. We showed that many metaheuristics have identical performance on problems which belong to the same structural class. In this paper, we define a notion of a distance between fitness functions. We argue that an algorithm cannot be efficient on a class of problems if the distance between the fitness function associated with instances of that class is too big. In [2] we corroborate our ideas using several problems.

References

[1]
Yossi Borenstein and Riccardo Poli. Structure and metaheuristics. GECCO 2006.
[2]
Yossi Borenstein and Riccardo Poli. Classes of problems in the black box scenario. Technical report, Department of Computer Science, University of Essex, 2006.
[3]
David Wolpert and William~G. Macready. No free lunch theorems for optimization. IEEE Trans. Evolutionary Computation, 1(1):67--82, 1997.
[4]
Yossi Borenstein and Riccardo Poli. Information landscapes and problem hardness. In GECCO '05: Proceedings of the 2005 conference on Genetic and evolutionary computation, pages 1425--1431, New York, NY, USA, 2005. ACM Press.

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    cover image ACM Conferences
    GECCO '06: Proceedings of the 8th annual conference on Genetic and evolutionary computation
    July 2006
    2004 pages
    ISBN:1595931864
    DOI:10.1145/1143997
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    Published: 08 July 2006

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    Author Tags

    1. genetic algorithms
    2. heuristics
    3. no free lunch
    4. theory

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    GECCO06
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    GECCO06: Genetic and Evolutionary Computation Conference
    July 8 - 12, 2006
    Washington, Seattle, USA

    Acceptance Rates

    GECCO '06 Paper Acceptance Rate 205 of 446 submissions, 46%;
    Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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