Advertisement

Automation and Remote Control

, Volume 68, Issue 5, pp 799–810 | Cite as

Parallelization of the quantile function optimization algorithms

  • A. I. Kibzun
Topical Issue
  • 34 Downloads

Abstract

Consideration was given to optimization of the loss function that is individually convex in the strategy and random vector. The problem was solved using the confidential method which majorizes the estimate of the quantile function. Two methods to determine the desired estimate were discussed. Both allow one to parallelize calculation of the estimate and reduce the problem to the solution of a set of convex programming problems.

PACS numbers

2.50.-r 02.60.Pn 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Kibzun, A.I. and Kan, Yu.S., Stochastic Programming Problems with Probability and Quantile Functions, Chichester: Wiley, 1996.zbMATHGoogle Scholar
  2. 2.
    Malyshev, V.V. and Kibzun, A.I., Analiz i sintez vysokotochnogo upravleniya LA (Analysis and Design of High-precision Control of Flight Vehicles), Moscow: Mashinostroenie, 1987.Google Scholar
  3. 3.
    Ermol’ev, Yu.M., Metody stokhasticheskogo programmirovaniya (Methods of Stochastic Programming), Moscow: Nauka, 1976.zbMATHGoogle Scholar
  4. 4.
    Kibzun, A.I. and Naumov, A.V., Guaranteeing Algorithm to Solve the Guantile Optimization Problem, Kosm. Issled., 1995, vol. 33, no. 2, pp. 160–165.Google Scholar
  5. 5.
    Kibzun, A.I. and Kurbakovskiy, V.Yu., Guaranteeing Approach to Solving Quantile Optimization Problems, Ann. Oper. Res., 1991, vol. 30, pp. 81–94.zbMATHCrossRefMathSciNetGoogle Scholar
  6. 6.
    Polyak, B.T., Vvedenie v optimizatsiyu, Moscow: Nauka, 1983. Translated into English under the title Introduction to Optimization, New York: Optimization Software, 1987.zbMATHGoogle Scholar

Copyright information

© Pleiades Publishing, Ltd. 2007

Authors and Affiliations

  • A. I. Kibzun
    • 1
  1. 1.Moscow State Aviation Institute (Technical University)MoscowRussia

Personalised recommendations