"On the Regularized Decomposition Method for Stochastic Programming Problems"

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Book	Author(s)	Year	Publisher
Stochastic Decomposition: A Statistical Method for Large Scale Stochastic Linear Programming	Julia L. Higle; Suvrajeet Sen	1996	Springer US
Stochastic Cauchy Problems in Infinite Dimensions: Generalized and Regularized Solutions	Irina V. Melnikova	2016	Routledge
Hodge Decomposition - A Method for Solving Boundary Value Problems	Günter Schwarz	1995	Springer Berlin Heidelberg
Solving Frontier Problems of Physics: The Decomposition Method	G. Adomian	1994	Springer Netherlands
Stability, Approximation, and Decomposition in Two- and Multistage Stochastic Programming	Christian Küchler	2009	Vieweg+Teubner Verlag
BONUS Algorithm for Large Scale Stochastic Nonlinear Programming Problems	Urmila Diwekar; Amy David	2015	Springer New York
Stochastic Programming: Modeling Decision Problems Under Uncertainty	Willem K. Klein Haneveld; Maarten H. van der Vlerk; Ward Romeijnders	1st ed. 2020	Springer International Publishing
Learn Bosque Programming: Discover the world's first regularized programming language	Sebastian Kaczmarek, Joel Ibaceta	2021	Packt Publishing
Stochastic Programming	András Prékopa	1995	Springer Netherlands
Stochastic Programming	Francesco Archetti; G. Di Pillo; M. Lucertini	1986	Springer Berlin Heidelberg
Stochastic Programming	A. Ruszczynski; and A. Shapiro	2003	Elsevier
Stochastic programming /	Kall, Peter.; Wallace, Stein W.,	[1994], ©1994.	Wiley,
Stochastic programming problems with probability and quantile functions /	Kibzun, A. I.; Kan, Yuri S.	[1996], ©1996.	Wiley,
Solving stochastic dynamic programming problems using rules of thumb	Anthony A. Smith	1991	Institute for Economic Research, Queen's University
Upper and Lower Bounds for Stochastic Processes: Decomposition Theorems	Michel Talagrand	2nd ed. 2021	Springer International Publishing
An enhanced decomposition algorithm for multistage stochastic hydroelectric scheduling	David P. Morton	1994	Naval Postgraduate School;Available from National Technical Information Service
Stochastic Linear Programming	P. Kall	1976	Springer Berlin Heidelberg
Stochastic linear programming	Peter Kall	1976	Springer-Verlag
Stochastic decision model for arithmetic programming	Mohammad Zia-Ul Haque	1976	Naval Postgraduate School
The Stochastic Perturbation Method for Computational Mechanics	Marcin Kamiński	2013	John Wiley & Sons
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Chapter	Author(s)	Book	Book Authors	Year	Publisher
On the Regularized Decomposition Method for Stochastic Programming Problems	Andrzej Ruszczyński	Stochastic Programming: Numerical Techniques and Engineering Applications	Kurt Marti; Peter Kall	1995	Springer Berlin Heidelberg
Regularized Decomposition and Augmented Lagrangian Decomposition for Angular Linear Programming Problems	Andrzej Ruszczynski	Aspiration Based Decision Support Systems: Theory, Software and Applications	Andrzej Lewandowski; Andrzej P. Wierzbicki	1989	Springer Berlin Heidelberg
Scenario Updating Method for Stochastic Mixed-integer Programming Problems	Guglielmo Lulli; Suvrajeet Sen	Operations Research Proceedings 2002: Selected Papers of the International Conference on Operations Research (SOR 2002), Klagenfurt, September 2–5, 2002	Ulrike Leopold-Wildburger; Franz Rendl; Gerhard Wäscher	2003	Springer Berlin Heidelberg
On Solving Stochastic Linear Programming Problems	P. Kall; J. Mayer	Stochastic Programming Methods and Technical Applications: Proceedings of the 3rd GAMM/IFIP-Workshop on “Stochastic Optimization: Numerical Methods and Technical Applications” held at the Federal Armed Forces University Munich, Neubiberg/München, Germany, June 17–20, 1996	Kurt Marti; Peter Kall	1998	Springer Berlin Heidelberg
On Complexity of Stochastic Programming Problems	Alexander Shapiro; Arkadi Nemirovski	Continuous Optimization: Current Trends and Modern Applications	V. Jeyakumar; Alexander M. Rubinov	2005	Springer US
Decomposition Methods for Linear Programming Problems	B. S. Razumikhin	Physical Models and Equilibrium Methods in Programming and Economics	B.S. Razumikhin	1984	Springer Netherlands
MinMax Stochastic Programming problems		Information-based complexity of convex programming	Nemirovski A	1995
A Sensitivity Method for Solving Multistage Stochastic Linear Programming Problems	Jacek Gondzio; Andrzej Ruszczynski	Aspiration Based Decision Support Systems: Theory, Software and Applications	Andrzej Lewandowski; Andrzej P. Wierzbicki	1989	Springer Berlin Heidelberg
On the Penalization Method in Convex Stochastic Programming	G. Ch. Pflug	Operations Research in Progress	Gustav Feichtinger; Peter Kall	1982	Springer Netherlands
The Stochastic Method for Solving Inverse Problems	Ne-Zheng Sun	Inverse Problems in Groundwater Modeling	Ne-Zheng Sun	1999	Springer Netherlands
On the approximation of stochastic convex programming problems	R. Lepp	Stochastic Optimization: Proceedings of the International Conference, Kiev, 1984	Vadim I. Arkin; A. Shiraev; R. Wets	1986	Springer Berlin Heidelberg
Discovering regularized programming		Learn Bosque Programming: Discover the world's first regularized programming language	Sebastian Kaczmarek, Joel Ibaceta	2021	Packt Publishing
Deterministic nonlinear programming equivalents for stochastic linear programming problems		Selected applications of nonlinear programming	Jerome Bracken, Garth P. McCormick	1968	Wiley
The Perturbation Method in Stochastic Programming	A. A. Pervozvanskii; V. G. Gaitsgori	Theory of Suboptimal Decisions: Decomposition and Aggregation	A. A. Pervozvanskii; V. G. Gaitsgori	1988	Springer Netherlands
Lagrange multipliers for the problems of stochastic programming	I. V. Evstigneev	Warsaw Fall Seminars in Mathematical Economics 1975	Maria Łoś; Jerzy Łoś; Andrzej Wieczorek	1976	Springer Berlin Heidelberg
A method of aggregate stochastic subgradients with on-line stepsize rules for convex stochastic programming problems	Andrzej Ruszczyński; Wojciech Syski	Stochastic Programming 84, Part II	A. Prékopa; Roger J.-B. Wets	1986	Springer Berlin Heidelberg
An Ergodic Theorem for Stochastic Programming Problems	Lisa A. Korf; Roger J-B Wets	Optimization: Proceedings of the 9th Belgian-French-German Conference on Optimization Namur, September 7–11, 1998	Van Hien Nguyen; Jean-Jacques Strodiot; Patricia Tossings	2000	Springer Berlin Heidelberg
Stochastic Programming Models for Vehicle Routing Problems	Baoding Liu and K. K. Lai	Focus on computational neurobiology /	Li, Lei.	[2004], ©2004.	Nova Science Publishers,
Approximation of Stochastic Programming Problems	Christine Choirat; Christian Hess; Raffaello Seri	Monte Carlo and Quasi-Monte Carlo Methods 2004	Harald Niederreiter; Denis Talay	2006	Springer Berlin Heidelberg
Two-Stage Stochastic Programming Problems	András Prékopa	Stochastic Programming	András Prékopa	1995	Springer Netherlands
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