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General Quadratic Programming and Its Applications in Response Surface Analysis

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Optimization and Optimal Control

Part of the book series: Springer Optimization and Its Applications ((SOIA,volume 39))

Summary

In this chapter, we consider the response surface problems that are formulated as the general quadratic programming. The general quadratic programming is split into convex quadratic maximization, convex quadratic minimization, and indefinite quadratic programming. Based on optimality conditions, we propose finite algorithms for solving those problems. As application, some real practical problems arising in the response surface, one of the main part of design of experiment, have been solved numerically by the algorithms.

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Author information

Authors and Affiliations

  1. Department of Mathematics, School of Economics Studies, National University of Mongolia, Ulaanbaatar, Mongolia

    Rentsen Enkhbat

  2. Department of Econometrics, School of Computer Science and Management, Mongolian University of Science and Technology, Ulaanbaatar, Mongolia

    Yadam Bazarsad

Authors
  1. Rentsen Enkhbat
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  2. Yadam Bazarsad
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Corresponding author

Correspondence to Rentsen Enkhbat .

Editor information

Editors and Affiliations

  1. South Kensington Campus, London, SW7 2AZ, United Kingdom

    Altannar Chinchuluun

  2. Dept. Industrial & Systems, Engineering, University of Florida, Weil Hall 303, Gainesville, 32611-6595, Florida, USA

    Panos M. Pardalos

  3. The School of Economic Studies, Dept.of Mathematics & Computer Science, National University of Mongolia, Ulaanbaatar, 210646, Mongolia

    Rentsen Enkhbat

  4. Labo. PRISM, Université Versailles, av. des Etats-Unis 45, Versailles CX, 78035, France

    Ider Tseveendorj

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Enkhbat, R., Bazarsad, Y. (2010). General Quadratic Programming and Its Applications in Response Surface Analysis. In: Chinchuluun, ., Pardalos, P., Enkhbat, R., Tseveendorj, I. (eds) Optimization and Optimal Control. Springer Optimization and Its Applications(), vol 39. Springer, New York, NY. https://doi.org/10.1007/978-0-387-89496-6_6

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