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Robust solutions of uncertain linear programs

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TLDR
It is shown that the RC of an LP with ellipsoidal uncertainty set is computationally tractable, since it leads to a conic quadratic program, which can be solved in polynomial time.
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This article is published in Operations Research Letters.The article was published on 1999-08-01 and is currently open access. It has received 1809 citations till now. The article focuses on the topics: Uncertain data & Linear programming.

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Planning Solid Waste Collection with Robust Optimization: Location-Allocation, Receptacle Type, and Service Frequency

TL;DR: A mathematical programming model is developed to minimize the costs that the purchaser pays to the waste management provider, subject to a level of service that is sufficient to collect all of the purchaser’s required waste.
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A box-uncertainty in DEA: A robust performance measurement framework

TL;DR: In this paper , the authors proposed a robust version of the CCR model for box-uncertainty data, where inputs and outputs are reported in the form of intervals and the robust counterpart problem for the envelopment form of the DEA model was formulated.
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Specifications of fundamental diagrams for dynamic traffic modeling

TL;DR: The difficulty in modeling congested traffic with single-valued fundamental diagrams and fine-grained loop detector data is highlighted and the effect of data granularity on model calibration and application is discussed.
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A resilience optimization approach for workforce-inventory control dynamics under uncertainty

TL;DR: A resilience optimization model is proposed for the dynamic workforce-inventory control problem wherein inventory planning, production releases, and workforce hiring decisions need to be made and a novel local search procedure is developed that combines the strengths of recent developments in robust optimization technology and small signal stability analysis of dynamic systems.
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Risk-sensitive control of cash management systems

TL;DR: A multiobjective model to control cash management systems with multiple accounts characterized by generalized cash flow processes, which replaces the customary use of bounds with cash balance reference trajectories and shows that tuning a parameter of the model can be of help to find more robust cash management policies.
References
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Book

Robust and Optimal Control

TL;DR: This paper reviewed the history of the relationship between robust control and optimal control and H-infinity theory and concluded that robust control has become thoroughly mainstream, and robust control methods permeate robust control theory.
BookDOI

Introduction to Stochastic Programming

TL;DR: This textbook provides a first course in stochastic programming suitable for students with a basic knowledge of linear programming, elementary analysis, and probability to help students develop an intuition on how to model uncertainty into mathematical problems.
Journal Article

Robust and Optimal Control

Kemin Zhou, +2 more
- 01 Jan 1997 - 
Book

Interior-Point Polynomial Algorithms in Convex Programming

TL;DR: This book describes the first unified theory of polynomial-time interior-point methods, and describes several of the new algorithms described, e.g., the projective method, which have been implemented, tested on "real world" problems, and found to be extremely efficient in practice.
Journal ArticleDOI

Robust Convex Optimization

TL;DR: If U is an ellipsoidal uncertainty set, then for some of the most important generic convex optimization problems (linear programming, quadratically constrained programming, semidefinite programming and others) the corresponding robust convex program is either exactly, or approximately, a tractable problem which lends itself to efficientalgorithms such as polynomial time interior point methods.
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