scholarly journals A class of derivative-free trust-region methods with interior backtracking technique for nonlinear optimization problems subject to linear inequality constraints

2018 ◽  
Vol 2018 (1) ◽  
Author(s):  
Jing Gao ◽  
Jian Cao
Keyword(s):  
Nonlinear Optimization ◽  
Linear Inequality ◽  
Optimization Problems ◽  
Trust Region ◽  
Inequality Constraints ◽  
Trust Region Methods ◽  
Linear Inequality Constraints ◽  
Derivative Free

A CONVEX APPROXIMATION METHOD FOR LARGE SCALE LINEAR INEQUALITY CONSTRAINED MINIMIZATION

2010 ◽  
Vol 27 (01) ◽  
pp. 85-101
Author(s):  
HAI-JUN WANG ◽  
QIN NI
Keyword(s):  
Large Scale ◽  
Linear Inequality ◽  
Trust Region ◽  
Inequality Constraints ◽  
New Method ◽  
Approximation Properties ◽  
Linear Inequality Constraints ◽  
Method Of Moving Asymptotes ◽  
Large Scale Problems ◽  
Moving Asymptotes

A new method of moving asymptotes for large scale minimization subject to linear inequality constraints is discussed in this paper. In each step of the iterative process, a descend direction is obtained by solving a convex separable subproblem with dual technique. The new rules for controlling the asymptotes parameters are designed by the trust region radius and some approximation properties such that the global convergence of the new method are obtained. The numerical results show that the new method may be capable of processing some large scale problems.

scholarly journals BRANCH AND BOUND WITH SIMPLICIAL PARTITIONS FOR GLOBAL OPTIMIZATION

2008 ◽  
Vol 13 (1) ◽  
pp. 145-159 ◽  
Author(s):  
J. Žilinskas
Keyword(s):  
Global Optimization ◽  
Branch And Bound ◽  
Linear Inequality ◽  
Optimization Problems ◽  
Inequality Constraints ◽  
Combinatorial Approach ◽  
Rectangular Shape ◽  
Linear Inequality Constraints ◽  
Advantages And Disadvantages ◽  
Branch And Bound Methods

Branch and bound methods for global optimization are considered in this paper. Advantages and disadvantages of simplicial partitions for branch and bound are shown. A new general combinatorial approach for vertex triangulation of hyper‐rectangular feasible regions is presented. Simplicial partitions may be used to vertex triangulate feasible regions of non rectangular shape defined by linear inequality constraints. Linear inequality constraints may be used to avoid symmetries in optimization problems.

Parameterize the Center of the Trust Region for Solving Quadratic Interpolation Models

2011 ◽  
Vol 52-54 ◽  
pp. 920-925
Author(s):  
Qing Hua Zhou ◽  
Yan Geng ◽  
Ya Rui Zhang ◽  
Feng Xia Xu
Keyword(s):  
Optimization Problems ◽  
Trust Region Method ◽  
Main Idea ◽  
Trust Region ◽  
Search Region ◽  
Trust Region Algorithm ◽  
Unconstrained Optimization Problems ◽  
Simplex Search ◽  
Quadratic Interpolation ◽  
Derivative Free

The derivative free trust region algorithm was considered for solving the unconstrained optimization problems. This paper introduces a novel methodology that modified the center of the trust region in order to improve the search region. The main idea is parameterizing the center of the trust region based on the ideas of multi-directional search and simplex search algorithms. The scope of the new region was so expanded by introducing a parameter as to we can find a better descent directions. Experimental results reveal that the new method is more effective than the classic trust region method on the testing problems.

scholarly journals A Nonmonotone Trust Region Algorithm Based on the Average of the Successive Penalty Function Values for Nonlinear Optimization

2013 ◽  
Vol 2013 ◽  
pp. 1-7
Author(s):  
Zhensheng Yu ◽  
Jinhong Yu
Keyword(s):  
Global Convergence ◽  
Penalty Function ◽  
Optimization Problems ◽  
Trust Region ◽  
Trust Region Methods ◽  
Constrained Optimization Problems ◽  
Trust Region Algorithm ◽  
Numerical Tests ◽  
Equality Constrained Optimization ◽  
Nonlinear Equality

We present a nonmonotone trust region algorithm for nonlinear equality constrained optimization problems. In our algorithm, we use the average of the successive penalty function values to rectify the ratio of predicted reduction and the actual reduction. Compared with the existing nonmonotone trust region methods, our method is independent of the nonmonotone parameter. We establish the global convergence of the proposed algorithm and give the numerical tests to show the efficiency of the algorithm.

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