Stochastic Dynamic Cutting Plane for Multistage Stochastic Convex Programs

نویسندگان

چکیده

We introduce Stochastic Dynamic Cutting Plane (StoDCuP), an extension of the Dual Programming (SDDP) algorithm to solve multistage stochastic convex optimization problems. At each iteration, builds lower bounding affine functions not only for cost-to-go functions, as SDDP does, but also some or all nonlinear cost and constraint functions. show almost sure convergence StoDCuP. inexact variant StoDCuP where subproblems are solved approximately (with bounded errors) this vanishing errors. Finally, numerical experiments presented on nondifferentiable programs Inexact computes a good approximate policy quicker than while previous combined with Mosek library were able differentiable reformulation problem.

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ژورنال

عنوان ژورنال: Journal of Optimization Theory and Applications

سال: 2021

ISSN: ['0022-3239', '1573-2878']

DOI: https://doi.org/10.1007/s10957-021-01842-x