Stochastic linear programming
C. Millham
- 01 Jan 1962
About: The article was published on 01 Jan 1962. and is currently open access. The article focuses on the topics: Inductive programming & Stochastic programming.
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
•Book
Lectures on Stochastic Programming: Modeling and Theory
Alexander Shapiro,Darinka Dentcheva,Andrzej Ruszczyński +2 more
- 24 Sep 2009
TL;DR: The authors dedicate this book to Julia, Benjamin, Daniel, Natan and Yael; to Tsonka, Konstatin and Marek; and to the Memory of Feliks, Maria, and Dentcho.
2.9K
From CVaR to Uncertainty Set: Implications in Joint Chance-Constrained Optimization
TL;DR: The approach builds on a classical worst-case bound for order statistics problems and is applicable even if the constraints are correlated, and provides an application of the model on a network resource allocation problem with uncertain demand.
A simulation-based approach to two-stage stochastic programming with recourse
TL;DR: In this paper, a statistical inference is developed and applied to estimation of the error, validation of optimality of a calculated solution and statistically based stopping criteria for an iterative alogrithm for two-stage stochastic programming with recourse where the random data have a continuous distribution.
The scenario approach for Stochastic Model Predictive Control with bounds on closed-loop constraint violations
TL;DR: A novel SCMPC method can be devised for general linear systems with additive and multiplicative disturbances, for which the number of scenarios is significantly reduced.
311
A multi-stage stochastic programming approach for production planning with uncertainty in the quality of raw materials and demand
TL;DR: In this article, a multi-product, multi-period production planning problem with uncertainty in the quality of raw materials and consequently in processes yields, as well as uncertainty in products demands is studied.
References
Chance-Constrained Programming
TL;DR: The paper presents a method of attack which splits the problem into two non-linear or linear programming parts, i determining optimal probability distributions, ii approximating the optimal distributions as closely as possible by decision rules of prescribed form.
2.7K
Cost Horizons and Certainty Equivalents: An Approach to Stochastic Programming of Heating Oil
TL;DR: In this paper, an integrated series of operations research studies directed toward improvement in such scheduling methods is presented. But the focus is on essentials of the mathematical model and other phases of the OR studies are brought in only as required.
699
Mathematical Programming of Portfolio Selections
TL;DR: This article is divided into four parts and contains a heuristic introduction to the basic problem, a mathematical statement of Markowitz's theory of portfolio selection and its basic assumptions, and a summarization and critique of the theory, its limitations, and its possibilities as a guide to practical decision-making.
46