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Stochastic optimization problems with nondifferentiable cost functionals

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Abstract

In this paper, we examine a class of stochastic optimization problems characterized by nondifferentiability of the objective function. It is shown that, in many cases, the expected value of the objective function is differentiable and, thus, the resulting optimization problem can be solved by using classical analytical or numerical methods. The results are subsequently applied to the solution of a problem of economic resource allocation.

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Additional information

This work was supported by the National Science Foundation under Grant No. GK 29237.

Communicated by P. Varayia

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Bertsekas, D.P. Stochastic optimization problems with nondifferentiable cost functionals. J Optim Theory Appl 12, 218–231 (1973). https://doi.org/10.1007/BF00934819

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Keywords

  • Probability Measure
  • Convex Function
  • Optimal Control Problem
  • Directional Derivative
  • Differentiability Property