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A Comparison of Maximum-Seeking Methods

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  • Samuel H. Brooks

    (General Analysis Corporation, Los Angeles, California)

Abstract

The steepest ascent, univariate, factorial, and random methods for seeking maxima were compared by trying versions of them in several two-factor situations, with and without experimental error. Of the two sequential methods, the steepest ascent was better than the univariate. Of the nonsequential methods, the factorial was better than the random. The sequential methods were superior to the nonsequential.

Suggested Citation

  • Samuel H. Brooks, 1959. "A Comparison of Maximum-Seeking Methods," Operations Research, INFORMS, vol. 7(4), pages 430-457, August.
    • Handle: RePEc:inm:oropre:v:7:y:1959:i:4:p:430-457
    DOI: 10.1287/opre.7.4.430
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    Cited by:

    1. Azadivar, F. & Talavage, J., 1980. "Optimization of stochastic simulation models," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 22(3), pages 231-241.
    2. Boehlje, M. D. & Eisgruber, L. M., 1975. "A Decision Model For The Estate Management Problem," ISU General Staff Papers 197508010700001017, Iowa State University, Department of Economics.
    3. Barkema, Alan Dean, 1985. "Farm survival under uncertainty," ISU General Staff Papers 1985010108000017535, Iowa State University, Department of Economics.
    4. Carlsson, Marten & Hovmark, Bertil & Lindgren, Ingvar, 1969. "Recent Developments in Farm Planning: A Monte Carlo Method for the Study of Farm Planning Problems," Review of Marketing and Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 37(02), pages 1-24, June.

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