Springer Nature is making SARS-CoV-2 and COVID-19 research free. View research | View latest news | Sign up for updates

Estimating the rate of convergence of the random search method

  • 14 Accesses

This is a preview of subscription content, log in to check access.

Literature Cited

  1. 1.

    L. V. Kantorovich, “On the method of steepest descent,” Dokl. Akad. Nauk SSSR,56, 3 (1947).

  2. 2.

    L. A. Rastrigin, Random Search in Problems of Optimization of Multiparameter Systems [in Russian] Zinatne, Riga (1965).

  3. 3.

    S. M. Movshovich, “Random search and the gradient method in optimization problems,” Izv. Akad. Nauk SSSR, Tekh. Kibern., No. 6 (1966).

  4. 4.

    J. L. Doob, Stochastic Processes, Wiley, New York (1953).

  5. 5.

    E. G. Nikolaev, “On steepest descent based on the random m-gradient method,” Avtom. Vychisl. Tekh., No. 3 (1970)

  6. 6.

    E. G. Nikolaev, “On steepest descent with random selection of directions”, Avtom. Vychisl. Tekh., No. 5 (1970).

Download references

Additional information

Translated from Kibernetika, No. 4, pp. 55–58, July–August, 1974.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Shor, N.Z., Shchepakin, M.B. Estimating the rate of convergence of the random search method. Cybern Syst Anal 10, 615–618 (1974). https://doi.org/10.1007/BF01071540

Download citation


  • Operating System
  • Artificial Intelligence
  • System Theory
  • Search Method
  • Random Search