Journal ArticleDOI
Solving two-stage robust optimization problems using a column-and-constraint generation method
TLDR
A computational study on a two-stage robust location-transportation problem shows that the column-and-constraint generation algorithm performs an order of magnitude faster than existing Benders-style cutting plane methods.About:
This article is published in Operations Research Letters.The article was published on 2013-09-01. It has received 1010 citations till now. The article focuses on the topics: Robust optimization & Cutting-plane method.read more
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Tutorials on Advanced Optimization Methods
TL;DR: This material discusses how to reformulate a difficult problem to a solver-compatible form via convexification, linearization, and decomposition, so the original problem can be reliably solved by commercial/open-source software.
Journal ArticleDOI
Optimisation methods for dispatch and control of energy storage with renewable integration
TL;DR: In this paper , a review of the state-of-the-art approaches for strategic dispatch and control of energy storage units is presented, which can be classified into three major categories: multistage optimisation, online optimisation and multi-timescale optimisation.
Journal ArticleDOI
An Algorithmic Game Approach for Demand Side Management in Smart Grid with Distributed Renewable Power Generation and Storage
TL;DR: In this article, the problem of minimizing electricity cost and the peak system load in smart grids with distributed renewable energy resources is studied, and a distributed demand-side management algorithm is proposed to solve this problem.
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Capacity Expansion of Wind Power in a Market Environment With Topology Control
TL;DR: A stochastic bilevel mixed integer optimization model is developed to investigate the wind power generation planning problem in an electricity market environment with topology control operations and results show that topological control could be very helpful in reducing wind energy curtailment and improving the wind penetration level.
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Multistage Robust Mixed-Integer Optimization Under Endogenous Uncertainty
TL;DR: In this paper, a tractable reformulation of the robust mixed-integer optimization problem with decision-dependent uncertainty sets has been proposed, which allows to consider both continuous and integer recourse decisions that affect the uncertainty set.
References
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Journal ArticleDOI
The Price of Robustness
Dimitris Bertsimas,Melvyn Sim +1 more
TL;DR: In this paper, the authors propose an approach that attempts to make this trade-off more attractive by flexibly adjusting the level of conservatism of the robust solutions in terms of probabilistic bounds of constraint violations.
The price of the robustness
D Bertsimas,M Sim +1 more
TL;DR: An approach is proposed that flexibly adjust the level of conservatism of the robust solutions in terms of probabilistic bounds of constraint violations, and an attractive aspect of this method is that the new robust formulation is also a linear optimization problem, so it naturally extend to discrete optimization problems in a tractable way.
Journal ArticleDOI
Robust Convex Optimization
Aharon Ben-Tal,Arkadi Nemirovski +1 more
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.
Journal ArticleDOI
Generalized Benders decomposition
TL;DR: In this paper, the extremal value of the linear program as a function of the parameterizing vector and the set of values of the parametric vector for which the program is feasible were derived using linear programming duality theory.