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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State-of-the-art short-term electricity market operation with solar generation: A review
TL;DR: In this article, a thorough review of the electricity markets worldwide with solar energy is provided, and a variety of proposed mathematical solutions to the problem are also discussed, with the focus on the uncertainty-based market operations.
Journal ArticleDOI
Distributionally robust coordination optimization scheduling for electricity-gas-transportation coupled system considering multiple uncertainties
TL;DR: A distributionally robust optimization (DRO) model is proposed considering multiple uncertainties comprehensively for the multi-energy coupled system, and the traffic flow uncertainty is transformed as the charging load uncertainty while the gas consumption uncertainty by gas-fired units is regarded as the reserve capacity configuration of units.
Journal ArticleDOI
Robust storage loading problems with stacking and payload constraints
TL;DR: This work considers storage loading problems where items with uncertain weights have to be loaded into a storage area, taking into account stacking and payload constraints, and proposes strict and adjustable optimization models for finite and interval-based uncertainties.
Journal ArticleDOI
Ambulance Deployment With Relocation Through Robust Optimization
Ran Zhang,Bo Zeng +1 more
TL;DR: An uncertainty set-based approach to capture ambulance unavailability and to build the robust optimization models (with relocation recourse decisions) are provided and efficient algorithms are designed to support practical instances.
Journal ArticleDOI
Stochastic optimization approaches for elective surgery scheduling with downstream capacity constraints: Models, challenges, and opportunities
TL;DR: The art of formulating and solving a class of stochastic resource-constrained scheduling problems for elective surgery scheduling and downstream capacity planning is described and areas of opportunity for developing tractable, implementable, and data-driven approaches that might be applicable within and outside healthcare operations.
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.