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A synthesis of optimal stopping time in compact genetic algorithm based on real options approach

Published: 07 July 2007 Publication History

Abstract

This paper introduces the real options approach, which is an evaluation tool for investment under uncertainty, to analyze optimal stopping time in genetic algorithms. This paper focuses on the simple model of EDAs named the compact genetic algorithm. This algorithm employs the probability vector as a model that scales well with the problem size. We analyze optimal stopping time of trap problems and propose an optimal stopping criterion as a decision contour. The proposed criterion also provides a stopping boundary, where termination is optimal on one side and continuation is on the other. This region suggests when it is worth continuing the algorithm and helps save computational effort by stopping early. Moreover, when the reset method is applied, the algorithm can reach a higher solution quality. The proposed technique can also be applied to analyze other problems.

References

[1]
Rimcharoen, S., Sutivong, D. and Chongstitvatana, P. Real options approach to finding optimal stopping time in compact genetic algorithm, In Proceedings of IEEE International Conference on Systems, Man, and Cybernetics, 2006.
[2]
Harik, G. R., Lobo, F. G. and Goldberg, D. E. The compact genetic algorithm, IEEE Trans. on Evolutionary Computation, 1999, 3(4): 287--297.

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    cover image ACM Conferences
    GECCO '07: Proceedings of the 9th annual conference on Genetic and evolutionary computation
    July 2007
    2313 pages
    ISBN:9781595936974
    DOI:10.1145/1276958

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    Association for Computing Machinery

    New York, NY, United States

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    Published: 07 July 2007

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    Author Tags

    1. genetic algorithms
    2. optimal stopping time
    3. real options

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    GECCO '07 Paper Acceptance Rate 266 of 577 submissions, 46%;
    Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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