A Stochastic Trust Region Method for Unconstrained Optimization Problems

In this paper, a stochastic trust region method is proposed to solve unconstrained minimization problems with stochastic objectives. Particularly, this method can be used to deal with nonconvex problems. At each iteration, we construct a quadratic model of the objective function. In the model, stoch...

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Veröffentlicht in:	Mathematical problems in engineering 2019-01, Vol.2019 (2019), p.1-10
Hauptverfasser:	Wang, Jing, Sun, Wenyu, Xue, Dan, Li, Ningning
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial intelligence Economic models Information processing International conferences Iterative methods Mathematical models Mathematical programming Methods Nonlinear programming Numerical analysis Optimization algorithms Random variables Signal processing Trust
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