Results 11 to 20 of about 947,067 (264)
Validating Sample Average Approximation Solutions with Negatively Dependent Batches [PDF]
, 2014 Sample-average approximations (SAA) are a practical means of finding approximate solutions of stochastic programming problems involving an extremely large (or infinite) number of scenarios. SAA can also be used to find estimates of a lower bound on the optimal objective value of the true problem which, when coupled with an upper bound, provides ...
Chen, Jiajie +4 more
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A hybrid genetic algorithm for scheduling jobs sharing multiple resources under uncertainty
EURO Journal on Computational Optimization, 2022 This study addresses the scheduling problem where every job requires several types of resources. At every point in time, the capacity of resources is limited. When necessary, the capacity can be increased at a cost.
Hanyu Gu, Hue Chi Lam, Yakov Zinder
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Applied Sciences, 2023 This paper critically examines the weighted sample average approximation (wSAA) framework, a widely used approach in prescriptive analytics for managing uncertain optimization problems featuring non-linear objectives.
Shuaian Wang, Xuecheng Tian
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A Sample Average Approximation Approach for Event-Driven Probabilistic Constraint Programming [PDF]
, 2005 We calculate the density profiles and density correlation functions of the one-dimensional Bose gas in a harmonic trap, using the exact finite-temperature solutions for the uniform case, and applying a local density approximation.
Hnich, B. +3 more
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On Feasibility of Sample Average Approximation Solutions [PDF]
SIAM Journal on Optimization, 2020 When there are infinitely many scenarios, the current studies of two-stage stochastic programming problems rely on the relatively complete recourse assumption. However, such assumption can be unrealistic for many real-world problems. This motivates us to study general stochastic programming problems where the sample average approximation (SAA ...
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Statistical modeling for laser induced damage threshold
Computational Science and Techniques, 2021 Monte Carlo experiments are an efficient tool for investigation of the Laser-Induced Damage Threshold (LIDT) testing with pulsed lasers. In this study, the approach of sequential Monte Carlo search is developed for LIDT testing with bundle of laser ...
Leonidas Sakalauskas +1 more
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Neutron thermal cross sections of 3D-printing organic polymers using the Average Functional Group Approximation [PDF]
EPJ Web of Conferences, 2023 We provide a worked example on how to obtain the total neutron scattering cross section of organic polymers at thermal neutron energies by means of the Average Functional Group Approximation.
Romanelli Giovanni +5 more
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Asymptotic Analysis for One-Stage Stochastic Linear Complementarity Problems and Applications
Mathematics, 2023 One-stage stochastic linear complementarity problem (SLCP) is a special case of a multi-stage stochastic linear complementarity problem, which has important applications in economic engineering and operations management.
Shuang Lin, Jie Zhang, Chen Qiu
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Non-asymptotic confidence bounds for the optimal value of a stochastic program [PDF]
, 2016 We discuss a general approach to building non-asymptotic confidence bounds for stochastic optimization problems. Our principal contribution is the observation that a Sample Average Approximation of a problem supplies upper and lower bounds for the ...
Guigues, Vincent +2 more
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Journal of Inequalities and Applications, 2023 In this paper, a class of stochastic vector variational inequality (SVVI) problems are considered. By employing the idea of a D-gap function, the SVVI problem is reformulated as a deterministic model, which is an unconstrained expected residual ...
Dan-dan Dong, Guo-ji Tang, Hui-ming Qiu
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