Abstract
For purposes of preliminary discussion, it is convenient to identify stochastic optimization problems with:
where ξ is a random N-vector with distribution function, P, f:Rn x RN → R U +∞ is a lower semicontinuous function, possibly convex, where dom f(.ξ) = x |f(x,ξ) is finite, corresponds to the set of acceptable choices for x when ξ is the observed value of the random vector ξ, and
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Keywords
- Stochastic Program
- Stochastic Optimization
- Discrete Distribution
- Probabilistic Constraint
- Lower Semicontinuous Function
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© 1985 Springer-Verlag Berlin Heidelberg
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Wets, R.J.B. (1985). Algorithmic Procedures for Stochastic Optimization. In: Schittkowski, K. (eds) Computational Mathematical Programming. NATO ASI Series, vol 15. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-82450-0_11
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DOI: https://doi.org/10.1007/978-3-642-82450-0_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-82452-4
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