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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Multi-objective robust energy management for all-electric shipboard microgrid under uncertain wind and wave
Sidun Fang,Yan Xu +1 more
TL;DR: A new robust energy management model is proposed to coordinately schedule an all-electric ship's power generation and voyage considering the uncertain wave and wind, and can fully guarantee the on-time rates of AES in various uncertain scenarios and providing high-quality Pareto solutions.
Journal ArticleDOI
Coordinated operation and expansion planning for multiple microgrids and active distribution networks under uncertainties
TL;DR: A robust model to solve the coordinated operation and expansion planning of active distribution networks with multiple microgrids, distributed energy resources, demand response, and N-1 generation contingency, formulated as a tri-level problem that is solved using a two-stage robust optimization approach.
Journal ArticleDOI
Climate‐aware generation and transmission expansion planning: A three‐stage robust optimization approach
TL;DR: A variant of the nested column-and-constraint-generation algorithm is proposed with global-optimality guarantee in a finite number of steps to solve the three-stage robust generation and transmission expansion planning model considering generation profiles of renewable energy sources affected by different long-term climate states.
Journal ArticleDOI
Two-Stage Planning of Network-Constrained Hybrid Energy Supply Stations for Electric and Natural Gas Vehicles
TL;DR: The concept and the formulation of a planning model for hybrid energy supply stations (HESSes) to supply EVs and NGVs and coordinates the three networks for attaining a higher operational flexibility and lower investment cost for HESS is proposed.
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Designing networks with resiliency to edge failures using two-stage robust optimization
TL;DR: This work designs resilient single-commodity flow networks that can remain robust against multiple concurrent edge failures, and proposes a column and constraint generation algorithm that can be applied to a defender versus attacker context, via the use of a decision-dependent 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.
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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.