Results 11 to 20 of about 2,320,712 (255)
Energy Reports, 2022 The deployment of a microgrid with renewable energy sources (RESs) generally considers two aspects i.e., the need for the energy storage and the presence of many uncertainties due to the intermittent nature of several RESs and the load demand variability.
Firmansyah Nur Budiman +6 more
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Quantitative Stability of Optimization Problems with Stochastic Constraints
Mathematics, 2023 In this paper, we consider optimization problems with stochastic constraints. We derive quantitative stability results for the optimal value function, the optimal solution set and the feasible solution set of optimization models in which the underlying ...
Wei Ouyang, Kui Mei
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Advances in Difference Equations, 2020 The spread of an epidemic diseases is stochastic in nature. It is more realistic to include this stochasticity when modelling the dynamics of a communicable disease.
Kamaleldin Abodayeh +5 more
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A Stochastic Multiobjective Optimization Framework for Wireless Sensor Networks
EURASIP Journal on Wireless Communications and Networking, 2010 In wireless sensor networks (WSNs), there generally exist many different objective functions to be optimized. In this paper, we propose a stochastic multiobjective optimization approach to solve such kind of problem.
Shibo He +5 more
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Optimal Stochastic Planarization [PDF]
2010 IEEE 51st Annual Symposium on Foundations of Computer Science, 2010 It has been shown by Indyk and Sidiropoulos [IS07] that any graph of genus g>0 can be stochastically embedded into a distribution over planar graphs with distortion 2^O(g). This bound was later improved to O(g^2) by Borradaile, Lee and Sidiropoulos [BLS09]. We give an embedding with distortion O(log g), which is asymptotically optimal.
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Stochastic programming with multivariate second order stochastic dominance constraints with applications in portfolio optimization [PDF]
, 2014 In this paper we study optimization problems with multivariate stochastic dominance constraints where the underlying functions are not necessarily linear. These problems are important in multicriterion decision making, since each component of vectors can
Xu, Huifu +2 more
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Modelling and solution methods for stochastic optimisation [PDF]
, 2011 This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.In this thesis we consider two research problems, namely, (i) language constructs for modelling stochastic programming (SP) problems and (ii) solution ...
Zverovich, Victor
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K-adaptability in stochastic optimization [PDF]
Mathematical Programming, 2022 AbstractWe consider stochastic problems in which both the objective function and the feasible set are affected by uncertainty. We address these problems using a K-adaptability approach, in which K solutions for a given problem are computed before the uncertainty dissolves and afterwards the best of them can be chosen for the realized scenario.
Malaguti E., Monaci M., Pruente J.
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Stochastic Saddle-Point Optimization for the Wasserstein Barycenter Problem
, 2022 We consider the population Wasserstein barycenter problem for random probability measures supported on a finite set of points and generated by an online stream of data.
Dvurechensky, Pavel +2 more
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Journal of Modern Power Systems and Clean Energy, 2017 This paper applies double-uncertainty optimization theory to the operation of AC/DC hybrid microgrids to deal with uncertainties caused by a high proportion of intermittent energy sources.
Peng LI +3 more
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