Results 71 to 80 of about 3,492,516 (198)
Robust Portfolio Optimization with a Hybrid Heuristic Algorithm [PDF]
Estimation errors in both the expected returns and the covariance matrix hamper the constructing of reliable portfolios within the Markowitz framework. Robust techniques that incorporate the uncertainty about the unknown parameters are suggested in the ...
Peter Winker, Björn Fastrich
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Robust high-cycle fatigue stress threshold optimization under uncertain loadings
Latin American Journal of Solids and StructuresThis paper proposes a strategy to achieve robust optimization of structures against high-cycle fatigue when a potentially large number of uncertain load cases are considered.
Alfredo R. de Faria +1 more
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Robust design methodologies: application to compressor blades
, 2006 Compressor blades are subtle aerodynamic shapes designed after years of research and insight. They inevitably show deviations from their desired shapes due to manufacturing errors, erosion or foreign object damage.
Kumar, Apurva
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A novel robust multi-objective evolutionary optimization algorithm based on surviving rate
Complex & Intelligent SystemsMulti-objective evolutionary optimization is widely utilized in industrial design. Despite the success of multi-objective evolutionary optimization algorithms in addressing complex optimization problems, research focusing on input disturbances remains ...
Wenxiang Jiang +3 more
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IEEE Access, 2018 In order to overcome the drawback of the conventional signal timing optimization, a robust optimization algorithm for signal control parameters based on Tabu search-artificial bee colony algorithm is proposed under unsaturated flow condition.
Wei Hao +4 more
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Calibration of Distributionally Robust Empirical Optimization Problems
, 2018 We study the out-of-sample properties of robust empirical optimization and develop a theory for data-driven calibration of the ``robustness parameter"" for worst-case maximization problems with concave reward functions.
Lim, Andrew
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Nonlinear distributionally robust optimization
Mathematical ProgrammingThis article focuses on a class of distributionally robust optimization (DRO) problems where, unlike the growing body of the literature, the objective function is potentially nonlinear in the distribution. Existing methods to optimize nonlinear functions in probability space use the Frechet derivatives, which present theoretical and computational ...
Mohammed Rayyan Sheriff +1 more
openaire +5 more sources
Mathematics, 2018 This paper deals with robust quasi approximate optimal solutions for a nonsmooth semi-infinite optimization problems with uncertainty data. By virtue of the epigraphs of the conjugates of the constraint functions, we first introduce a robust type closed ...
Xiangkai Sun, Hongyong Fu, Jing Zeng
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Approximated computation of belief functions for robust design optimization [PDF]
, 2012 This paper presents some ideas to reduce the computational cost of evidence-based robust design optimization. Evidence Theory crystallizes both the aleatory and epistemic uncertainties in the design parameters, providing two quantitative measures, Belief
Massimilano Vasile +5 more
core +2 more sources