scholarly journals An algorithm for LC1 optimization

2005 ◽  
Vol 15 (2) ◽  
pp. 301-306 ◽  
Author(s):  
Nada Djuranovic-Milicic
Keyword(s):  
Rate Of Convergence ◽  
Unconstrained Optimization ◽  
Optimization Problems ◽  
Directional Derivative ◽  
Second Order ◽  
General Algorithm ◽  
Unconstrained Optimization Problems ◽  
Convergence Proof

In this paper an algorithm for LC1 unconstrained optimization problems, which uses the second order Dini upper directional derivative is considered. The purpose of the paper is to establish general algorithm hypotheses under which convergence occurs to optimal points. A convergence proof is given, as well as an estimate of the rate of convergence.

scholarly journals A trust region algorithm for lc1 unconstrained optimization

Filomat ◽  
2007 ◽  
Vol 21 (2) ◽  
pp. 285-290
Author(s):  
Nada Djuranovic-Milicic
Keyword(s):  
Rate Of Convergence ◽  
Unconstrained Optimization ◽  
Directional Derivative ◽  
Trust Region ◽  
Second Order ◽  
Trust Region Algorithm ◽  
Lipschitzian Functions ◽  
Convergence Proof ◽  
Locally Lipschitzian Functions

In this paper a trust region algorithm for minimization of locally Lipschitzian functions, which uses the second order Dini upper directional derivative is considered. A convergence proof is given, as well as an estimate of the rate of convergence. .

scholarly journals A multi-step curve search algorithm in nonlinear optimization

2008 ◽  
Vol 18 (1) ◽  
pp. 47-52 ◽  
Author(s):  
Nada Djuranovic-Milicic
Keyword(s):  
Rate Of Convergence ◽  
Nonlinear Optimization ◽  
Unconstrained Optimization ◽  
Optimization Problems ◽  
Search Algorithm ◽  
Unconstrained Optimization Problems ◽  
Convergence Proof ◽  
Step Algorithm

In this paper a multi-step algorithm for LC1 unconstrained optimization problems is presented. This method uses previous multi-step iterative information and curve search to generate new iterative points. A convergence proof is given, as well as an estimate of the rate of convergence.

scholarly journals On an algorithm in C 1,1 optimization

Filomat ◽  
2007 ◽  
Vol 21 (1) ◽  
pp. 17-24
Author(s):  
Nada Djuranovic-Milicic
Keyword(s):  
Rate Of Convergence ◽  
Directional Derivative ◽  
Second Order ◽  
Convergence Proof

In this paper an algorithm for minimization of C 1,1 functions, which uses the second order Dini upper directional derivative is considered. The purpose of the paper is to establish for this algorithm general hypotheses under which convergence occurs to optimal points. A convergence proof is given, as well as an estimate of the rate of convergence.

A Non-Monotone Line Search Combination Technique for Unconstrained Optimization

2014 ◽  
Vol 8 (1) ◽  
pp. 218-221 ◽  
Author(s):  
Ping Hu ◽  
Zong-yao Wang
Keyword(s):  
Global Convergence ◽  
Unconstrained Optimization ◽  
Numerical Experiments ◽  
Line Search ◽  
Optimization Problems ◽  
Search Algorithm ◽  
New Combination ◽  
Combination Rule ◽  
Combination Technique ◽  
Unconstrained Optimization Problems

We propose a non-monotone line search combination rule for unconstrained optimization problems, the corresponding non-monotone search algorithm is established and its global convergence can be proved. Finally, we use some numerical experiments to illustrate the new combination of non-monotone search algorithm’s effectiveness.

Parallel-vector computation for linear structural analysis and non-linear unconstrained optimization problems

1991 ◽  
Vol 2 (2-3) ◽  
pp. 175-182 ◽  
Author(s):  
D.T. Nguyen ◽  
O.O. Storaasli ◽  
E.A. Carmona ◽  
M. Al-Nasra ◽  
Y. Zhang ◽  
...  
Keyword(s):  
Structural Analysis ◽  
Unconstrained Optimization ◽  
Optimization Problems ◽  
Unconstrained Optimization Problems ◽  
Non Linear
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