Polyhedral convex feasible regions in stochastic programming with recourse
- 1 December 1975
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
Abstract
Multistage stochastic programming with recourse is formulated in terms of a recursive sequence of mathematical programming problems--P0,..., PK--with stochastic data. A polyhedral property of their feasible regions is used to derive a Lipschitz property of their objective functions. A slightly stronger property is used to conclude that any measurable decision rule satisfying the explicit and Implicit constraints of Pk(0 ≤ k ≤ K) almost surely can be redefined on a set of measure 0 so it satisfies the constraints for every possible realization of the random variables. Sufficient conditions for each of the two polyhedral convexity properties are given.Keywords
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