Results 231 to 240 of about 295,852 (287)

Genomic optimum contribution selection and mate allocation using JuMP. [PDF]

Bioinform Adv
Waldmann P.
europepmc   +1 more source

A dual enhanced stochastic gradient descent method with dynamic momentum and step size adaptation for improved optimization performance. [PDF]

Sci Rep
Mokhtar MA, Fathy M, Dahab YA, Sayed EA.
europepmc   +1 more source

Flexible renewable integrated energy system capabilities to improve voltage stability with power quality and economic environmental operation of smart grid. [PDF]

Sci Rep
Hassankashi A, Dini A, Pirouzi S, Veisi M, Bahreini M.   +4 more
europepmc   +1 more source

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Stochastic Offline Programming

2009 21st IEEE International Conference on Tools with Artificial Intelligence, 2009
We propose a framework which we call stochastic off-line programming (SOP). The idea is to embed the development of combinatorial algorithms in an off-line learning environment which helps the developer choose heuristic advisors that guide the search for satisfying or optimal solutions.
YURI MALITSKY, MEINOLF SELLMANN
openaire   +1 more source

Asymptotic Stochastic Programs

Mathematics of Operations Research, 1995
Consider a stochastic program with unique solution. By the notion of epi-convergence in distribution in local coordinates, we define the asymptotic stochastic program associated to it. Stochastic programs may be classified according to the type of the pertaining asymptotic program.
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Stochastic Programming

Statistica Neerlandica, 1967
SummaryThis report presents an approach to stochastic programming. It treats mainly the difficulties arising in formulating the problem and the possibilities to derive a deterministic problem by which it can be replaced. In a sense the approach of this report unifies different viewpoints on stochastic programming problems as they have been published in
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Discrete Stochastic Programming

Management Science, 1968
A method is presented for solving linear programming problems where (any number of) the functional, restraint, and input-output coefficients are subject to discrete; probability distributions. The objective function is formulated in terms of variance and/or expectation.
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Periodical Multistage Stochastic Programs

SIAM Journal on Optimization, 2020
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Alexander Shapiro, Lingquan Ding
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Stochastic Programming

The Journal of the Operational Research Society, 1995
ANDREATTA, GIOVANNI, G. SALINETTI, R. WETS   +2 more
  +8 more sources