Decomposition and Partitioning Methods for Multistage Stochastic Linear Programs
نویسندگان
چکیده
منابع مشابه
Working Paper on Augmented Lagrangian Decomposition Methods for Multistage Stochastic Programs on Augmented Lagrangian Decomposition Methods for Multistage Stochastic Programs on Augmented Lagrangian Decomposition Methods for Multistage Stochastic Programs
A general decomposition framework for large convex optimization problems based on augmented Lagrangians is described. The approach is then applied to multistage stochastic programming problems in two di erent ways: by decomposing the problem into scenarios and by decomposing it into nodes corresponding to stages. Theoretical convergence properties of the two approaches are derived and a computa...
متن کاملSubtree decomposition for multistage stochastic programs
A number of methods for solving multistage stochastic linear programs with recourse decompose the deterministic equivalent [4] to form subproblems based on scenarios (e.g., Rockafellar and Wets [6] and Mulvey and Ruszczyński [5]). Other methods use forms of Benders decomposition to form subproblems based on nodes of the scenario tree (e.g., Birge [1] and Gassmann [2]). Both types of algorithms ...
متن کاملA New Decomposition Technique in Solving Multistage Stochastic Linear Programs by Infeasible Interior Point Methods
Multistage stochastic linear programming (MSLP) is a powerful tool for making decisions under uncertainty. A deteministic equivalent of MSLP is a large-scale linear program with nonanticipativity constraints. Recently developed infeasible interior point methods are used to solve the resulting linear program. Technical problems arising from this approach include rank reduction and computation of...
متن کاملOn Dynamic Decomposition of Multistage Stochastic Programs
It is well known that risk-averse multistage stochastic optimization problems are often not in the form of a dynamic stochastic program, i.e. are not dynamically decomposable. In this paper we demonstrate how some of these problems may be extended in such a way that they are accessible to dynamic algorithms. The key technique is a new recursive formulation for the Average Value-atRisk. To this ...
متن کاملScenario-Tree Decomposition: Bounds for Multistage Stochastic Mixed-Integer Programs
Multistage stochastic mixed-integer programming is a powerful modeling paradigm appropriate for many problems involving a sequence of discrete decisions under uncertainty; however, they are difficult to solve without exploiting special structures. We present scenario-tree decomposition to establish bounds for unstructured multistage stochastic mixed-integer programs. Our method decomposes the s...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Operations Research
سال: 1985
ISSN: 0030-364X,1526-5463
DOI: 10.1287/opre.33.5.989