Jinghui Liu, Changfeng Ma, A NEW NONMONOTONE TRUST REGION ALGORITHM FOR SOLVING UNCONSTRAINED OPTIMIZATION PROBLEMS, Journal of Computational Mathematics, Vol. 32, No. 4 (July 2014), pp. 476-490 ...

Description: Survey of computational tools for solving constrained and unconstrained nonlinear optimization problems. Emphasis on algorithmic strategies and characteristic structures of nonlinear ...

In this paper we test different conjugate gradient (CG) methods for solving largescale unconstrained optimization problems. The methods are divided in two groups: the first group includes five basic ...

Conjugate gradient methods form a class of iterative algorithms that are highly effective for solving large‐scale unconstrained optimisation problems. They achieve efficiency by constructing ...

The package CG+ is a Conjugate Gradient code for solving large-scale, unconstrained, nonlinear optimization problems. CG+ implements three different versions of the Conjugate Gradient method: the ...

The BFGS algorithm is an iterative method for unconstrained nonlinear optimization. Contrary to Newton’s method, it does not require the time-consuming calculation of the inverse Hessian matrix.

The course is designed to provide engineering students a view of optimization as a tool for engineering decision making. Students will be given a fundamental introduction to the optimization ...

Studies linear and nonlinear programming, the simplex method, duality, sensitivity, transportation and network flow problems, some constrained and unconstrained optimization theory, and the ...