Abstract

A general strong law of large numbers for stochastic programs is established. It is shown that solutions and approximate solutions may not be consistent with the strong law in general, but consistency holds locally, or when the decision space is compact. An additional integrability condition implies the uniform consistency of approximate solutions. The results are applied in the context of linear recourse models.

Author information

Contact details are reproduced from the original publication and may be historical.

Zvi Artstein

Department of Theoretical Mathematics, The Weizmann Institute of Science, Rehovot 76100, Israel.

Roger J-B Wets

Department of Mathematics, University of California, Davis, CA 95616, U.S.A.

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Suggested citation

Z. Artstein, R. J-B Wets. “Consistency of Minimizers and the SLLN for Stochastic Programs.” Journal of Convex Analysis 2 (1995), No. 1&2, 1–17. https://doi.org/10.68381/jca02001

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Published by Heldermann Verlag, 1995. Rights now held by Banach Press LLC.