Dealing with singularities in nonlinear unconstrained optimization

Dealing with singularities in nonlinear unconstrained optimization

Nonlinear transformations for the simplification of unconstrained nonlinear optimization problems

Formalization decisions in mathematical programming could significantly influence the complexity of the problem, and so the efficiency of the applied solver methods. This widely accepted statement induced investigations for the reformulation of optimization problems in the hope of getting easier to solve problem forms, e.g. in integer programming. These transformations usually go hand in hand w...

Open Problems in Nonlinear Conjugate Gradient Algorithms for Unconstrained Optimization

The paper presents some open problems associated to the nonlinear conjugate gradient algorithms for unconstrained optimization. Mainly, these problems refer to the initial direction, the conjugacy condition, the step length computation, new formula for conjugate gradient parameter computation based on function’s values, the influence of accuracy of line search procedure, how we can take the pro...

Recent progress in unconstrained nonlinear optimization without derivatives

A New Descent Nonlinear Conjugate Gradient Method for Unconstrained Optimization

In this paper, a new nonlinear conjugate gradient method is proposed for large-scale unconstrained optimization. The sufficient descent property holds without any line searches. We use some steplength technique which ensures the Zoutendijk condition to be held, this method is proved to be globally convergent. Finally, we improve it, and do further analysis.