An Adaptive Approximation Method for Stochastic, Dynamic Programs, with Applications to Inventory and Distribution Problems
نویسندگان
چکیده
We introduce a technique called Concave, Adaptive Value Estimation (CAVE) to approximate recourse functions found in stochastic programs. CAVE constructs a sequence of concave (or convex) piecewise-linear approximations using sample gradients of the recourse function at di erent points in the domain. The result is a nonlinear approximation that is more responsive than traditional stochastic quasi-gradient methods and more exible than analytical techniques. In addition, we demonstrate near-optimal behavior of the CAVE approximation in experiments involving three di erent types of stochastic programs | single point estimation of a function, the newsboy stochastic inventory problem, and two-stage distribution problems with network recourse.
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