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A method of minimizing an undifferentiable function with generalized-gradient averaging

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Literature Cited

  1. 1.

    A. M. Gupal, “Methods of minimizing functions that satisfy the Lipshits condition with averaging of the descent directions,” Kibernetika, No. 5, 49–51 (1978).

  2. 2.

    V. I. Norkin, “Nonlocal algorithms for minimizing undifferentiable functions,” Kibernetika, No. 5, 57–60 (1978).

  3. 3.

    V. I. Norkin, “Generalized differentiable functions,” Kibernetika, No. 1, 9–11 (1980).

  4. 4.

    E. A. Nurminskii, “A quasigradient method of solving problems in nonlinear programming,” Kibernetika, No. 1, 122–125 (1973).

  5. 5.

    E. A. Nurminskii and A. A. Gaivoronskii, “A nonstationary extremal problem,” in: Methods from Operational Research and Reliability Theory in Systems Analysis [in Russian], Inst. Kibern. Akad. Nauk UkrSSR, Kiev (1976), pp. 84–97.

  6. 6.

    Yu. M. Ermol'ev, Stochastic-Programming Methods [in Russian], Nauka, Moscow (1976).

  7. 7.

    A. A. Zhelikhovskii, “ε-Quasigradient methods for the solution of nonsmooth extremal problems and their implementation in a conversational-mode optimization system,” Candidate's Dissertation, Kiev (1979).

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Additional information

Translated from Kibernetika, No. 6, pp. 88–89, 102, November–December, 1980.

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Norkin, V.I. A method of minimizing an undifferentiable function with generalized-gradient averaging. Cybern Syst Anal 16, 890–892 (1980). https://doi.org/10.1007/BF01069064

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Keywords

  • Operating System
  • Artificial Intelligence
  • System Theory