Results 221 to 230 of about 555,552 (274)

A practical approach to replenishment optimization with extended (R, s, Q) policy and probabilistic models. [PDF]

Sci Rep
Presbitero A, Syrén A, Dippel H, Awasthi L, Dev S, Nie Z.   +5 more
europepmc   +1 more source

GeneDrive.jl: A decision tool to optimize biological vector control strategies under climate change. [PDF]

PLoS Comput Biol
Vásquez VN, Mordecai EA, Anthoff D.
europepmc   +1 more source

Correction to: "A Review of Global Optimization Methods for Molecular Structures: Algorithms, Applications and Perspectives". [PDF]

J Comput Chem
europepmc   +1 more source

Some of the next articles are maybe not open access.

Related searches:

Stochastic Discrete Optimization

SIAM Journal on Control and Optimization, 1992
Summary: A stochastic search method is proposed for finding a global solution to the stochastic discrete optimization problem in which the objective function must be estimated by Monte Carlo simulation. Although there are many practical problems of this type in the fields of manufacturing engineering, operations research, and management science, there ...
Yan, Di, Mukai, H.
openaire   +2 more sources

Stochastic Optimization: a Review

International Statistical Review, 2002
SummaryWe review three leading stochastic optimization methods—simulated annealing, genetic algorithms, and tabu search. In each case we analyze the method, give the exact algorithm, detail advantages and disadvantages, and summarize the literature on optimal values of the inputs. As a motivating example we describe the solution—using Bayesian decision
Fouskakis, Dimitris, Draper, David
openaire   +2 more sources

Stochastic Optimal Control

1987
In the long history of mathematics, stochastic optimal control is a rather recent development. Using Bellman’s Principle of Optimality along with measure-theoretic and functional-analytic methods, several mathematicians such as H. Kushner, W. Fleming, R. Rishel. W.M. Wonham and J.M.
openaire   +1 more source

Stochastic Optimization of Regulators

Computers & Structures, 2017
The optimal design of regulators is often based on the use of given, fixed nominal values of initial conditions, external loads and dynamic parameters of the control system. However, due to variations of material properties, tasks to be executed, modeling errors, etc., the model parameters are not exactly known and given quantities.
openaire   +1 more source

Stochastic optimal structural control: Stochastic optimal open-loop feedback control

Advances in Engineering Software, 2012
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +2 more sources

Evolutionary Stochastic Portfolio Optimization

2008
In this chapter, the concept of evolutionary stochastic portfolio optimization is discussed. Selected theory from the fields of Stochastic Programming, evolutionary computation, portfolio optimization, as well as financial risk management is used to derive a generalized framework for computing optimal financial portfolios given an uncertain future ...
openaire   +3 more sources

Adaptive Biased Stochastic Optimization

IEEE Transactions on Pattern Analysis and Machine Intelligence
This work develops and analyzes a class of adaptive biased stochastic optimization (ABSO) algorithms from the perspective of the GEneralized Adaptive gRadient (GEAR) method that contains Adam, AdaGrad, RMSProp, etc. Particularly, two preferred biased stochastic optimization (BSO) algorithms, the biased stochastic variance reduction gradient (BSVRG ...
openaire   +2 more sources