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A practical search index and population size analysis based on the building block hypothesis

Published: 12 July 2008 Publication History

Abstract

Use of the Building Block Hypothesis to illuminate GA search behavior, as pursued by J. H. Holland and D. E. Goldberg, invites additional investigation. This paper re-examines the space actually searched by a GA, in light of the Building Block Hypothesis, GA sampling and population size, in an effort to develop more quantitative measures of GA di±culty for problems where building block sizes can be estimated. A Practical Search Index (PSI) is defined, related to the size of the space actively searched by the GA, in terms of sizes and numbers of building blocks. When BBs are hierarchical, the PSI can be used at various stages of BB assembly. Difficulty depends strongly on the sizes of the largest building blocks, rather than on the size of the entire search space, for GAs dominated by crossover. Premature convergence prevails when population size is not adequate to allow sampling and assembly of building blocks. Appropriate sizing depends on balancing the BB sampling and mixing costs. A set of simple GA experiments on classical test functions with clear building block structures (One-Max, RR1, RR2, RRJH, HIFF, etc.) at various population sizes, illustrates the relationship between the PSI, population size, and efficiency of search.

References

[1]
D. E. Goldberg. Genetic Algorithms in Search, Optimization, and Machine Learning. Addison-Wesley Longman Publishing Co., Inc., Boston, MA, 1989.
[2]
J. H. Holland. Building blocks, cohort genetic algorithms, and hyperplane-defined functions. Evolutionary Computation, 8(4):373--391, 2000.

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    cover image ACM Conferences
    GECCO '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation
    July 2008
    1814 pages
    ISBN:9781605581309
    DOI:10.1145/1389095
    • Conference Chair:
    • Conor Ryan,
    • Editor:
    • Maarten Keijzer
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Publication History

    Published: 12 July 2008

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    Author Tags

    1. GA hardness
    2. building block sampling
    3. building blocks
    4. genetic algorithm
    5. population size
    6. practical search index
    7. search space

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