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
Citations
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Journal ArticleDOI
The Value of Flexibility in Robust Location–Transportation Problems
TL;DR: In this article, a capacitated fixed-charge multi-period location-transportation problem is studied, where the location and capacity of each facility must be determined immediately, while the determination of the final production and distribution of products can be delayed until actual orders are received in each period.
Journal ArticleDOI
A scalable and robust approach to demand side management for smart grids with uncertain renewable power generation and bi-directional energy trading
Ren-Shiou Liu,Yu Feng Hsu +1 more
TL;DR: Numerical results show that, although the C&CG method produces optimal solutions, the SRDSM algorithm is much more scalable and efficient when the problem size is large.
Journal ArticleDOI
Network-constrained unit commitment under significant wind penetration: A multistage robust approach with non-fixed recourse
TL;DR: The least-cost generation schedule ensuring dispatch nonanticipativity is attained by solving a trilevel program of similar complexity as compared with available formulations neglecting this aspect, and an enhanced column-and-constraint generation algorithm is devised whereby lexicographic optimization is applied to accelerate the finite convergence to optimality.
Journal ArticleDOI
Robust optimization for improving resilience of integrated energy systems with electricity and natural gas infrastructures
TL;DR: A three-stage robust optimization model is proposed for resilient operation of energy system which integrates electricity and natural gas transmission networks with the objective of minimizing load curtailments caused by attacks.
Journal ArticleDOI
Day-Ahead Contingency-Constrained Unit Commitment With Co-Optimized Post-Contingency Transmission Switching
TL;DR: Numerical simulations based on the IEEE 118- and 300-bus systems demonstrate the effective performance of the proposed approach as well as its economic and operational advantages over existing models disregarding post-contingency transmission switching.
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.