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Robust Combinatorial Optimization with Locally Budgeted Uncertainty
Open Journal of Mathematical Optimization, 2021 Budgeted uncertainty sets have been established as a major influence on uncertainty modeling for robust optimization problems. A drawback of such sets is that the budget constraint only restricts the global amount of cost increase that can be distributed
Goerigk, Marc, Lendl, Stefan
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Robust strong duality for nonconvex optimization problem under data uncertainty in constraint
AIMS Mathematics, 2021 This paper deals with the robust strong duality for nonconvex optimization problem with the data uncertainty in constraint. A new weak conjugate function which is abstract convex, is introduced and three kinds of robust dual problems are constructed to ...
Yanfei Chai
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Case Studies in Thermal Engineering, 2020 The Furnace Exit Gas Temperature (FEGT) is a key parameter of the combustion process in utility boilers that needs to be accurately monitored, especially in order to increase their load- and fuel-flexibility.
J. Blondeau +4 more
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Oracle-Based Robust Optimization via Online Learning [PDF]
, 2014 Robust optimization is a common framework in optimization under uncertainty when the problem parameters are not known, but it is rather known that the parameters belong to some given uncertainty set.
Ben-Tal, Aharon +3 more
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Non-Uniform Robust Network Design in Planar Graphs [PDF]
, 2015 Robust optimization is concerned with constructing solutions that remain feasible also when a limited number of resources is removed from the solution. Most studies of robust combinatorial optimization to date made the assumption that every resource is ...
Adjiashvili, David
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Theory and Applications of Robust Optimization [PDF]
, 2010 In this paper we survey the primary research, both theoretical and applied, in the area of Robust Optimization (RO). Our focus is on the computational attractiveness of RO approaches, as well as the modeling power and broad applicability of the ...
Banerjee O. +10 more
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Multipolar robust optimization
EURO Journal on Computational Optimization, 2018 We consider linear programs involving uncertain parameters and propose a new tractable robust counterpart which contains and generalizes several other models including the existing Affinely Adjustable Robust Counterpart and the Fully Adjustable Robust ...
Walid Ben-Ameur +3 more
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Multi-objective topology design optimization combined with robust optimization
Journal of Advanced Mechanical Design, Systems, and Manufacturing, 2023 Topology optimization (TO), which is a design optimization technique that does not require design parameters, has been attracting attention. TO has a high degree of freedom and can obtain a novel design shape suitable for desired purposes.
Akito MARUO +4 more
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Optimal Design of Electrically Fed Hybrid Mars Ascent Vehicle
Aerospace, 2021 The optimal design of the propulsion system for a potential Mars Ascent Vehicle is analyzed, in the context of the Mars Sample Return Mission. The Mars Ascent Vehicle has to perform an initial ascent phase from the surface and then circularize into a 170
Lorenzo Casalino +2 more
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Shortfall-Based Wasserstein Distributionally Robust Optimization
Mathematics, 2023 In this paper, we study a distributionally robust optimization (DRO) problem with affine decision rules. In particular, we construct an ambiguity set based on a new family of Wasserstein metrics, shortfall–Wasserstein metrics, which apply normalized ...
Ruoxuan Li, Wenhua Lv, Tiantian Mao
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