A special newton-type optimization method: Optimization: Vol 24, No 3-4doi:10.1080/02331939208843795Nonlinear Programming AlgorithmsInequality ConstraintsKuhn-Tucker PointsNewton’s MethodClarke’s JacobianStrict Complementary Slackness ConditionA. Fischer...
BFGS is a type of quasi-Newton method. It seeks to approximate the inverse of the Hessian using the function’s gradient information. This approximation is such that it does not involve second derivatives. Thus, this method has a slower convergence rate than Newton’s methods, although it is...
A quasi-Newton trust region method with a new conic model for the unconstrained optimization - ScienceDirect Lu, X., Ni, Q.: A quasi-Newton trust region method with a new conic model for the unconstrained optimization. Appl. Math. Comput. 204, 373-384 ... Xiaoping Lu a,Qin Ni b - ...
Optimization in Simulation is an important problem often encountered in system behavior investigation; however, the existing methods such as response surface methodology and stochastic approximation method are inefficient. This paper presents a modification of a quasi-Newton method, in which the parameters...
We introduce DeNT, a decentralized Newton-based tracking algorithm that solves and track the solution trajectory of continuously varying networked convex optimization problems. DeNT is derived from the prediction-correction methodology, by which the time-varying optimization problem is sampled at discrete ...
For the Lagrangian-DNN relaxation of quadratic optimization problems (QOPs), we propose a Newton-bracketing method to improve the performance of the bisection-projection method implemented in BBCPOP [to appear in ACM Tran. Softw., 2019]. The relaxation problem is converted into the problem of ...
摘要: The local quadratic convergence of the Gauss-Newton method for convex composite optimization is established for any convex function with a minimum set. This work extends Burke and Ferris' results when this minimum set is a set of weak sharp minima for the convex function....
We propose a Newton method for solving smooth unconstrained vector optimization problems under partial orders induced by general closed convex pointed cones. The method extends the one proposed by Fliege, Graa Drummond and Svaiter for multicriteria, which in turn is an extension of the classical New...
摘要: The local quadratic convergence of the Gauss-Newton method for convex composite optimization is established for any convex function with a minimum set. This work extends Burke and Ferris' results when this minimum set is a set of weak sharp minima for the convex function....
The script obtained these values from the ‘VmHWM’ record in the special file ‘/proc/[pid]/status’ provided32 by our GNU/Linux system, where ‘[pid]’ is the process identifier. The evaluation script also monitored the number of virtual memory pages transferred from the physical RAM to ...