the dogleg severity is one of the most important parameters in directional drilling. improvement of these indicators actually means choosing the best conditions for the directional drilling in order to reach the target point. selection of high levels of the dogleg severity actually means minimizing well trajectory, but on the other hand, increases fatigue in drill string, increases torque and d...

The dogleg severity is one of the most important parameters in directional drilling. Improvement of these indicators actually means choosing the best conditions for the directional drilling in order to reach the target point. Selection of high levels of the dogleg severity actually means minimizing well trajectory, but on the other hand, increases fatigue in drill string, increases torque and d...

This paper describes a method of dogleg trust-region steps, or restricted Levenberg-Marquardt steps, based on a projection process onto the Krylov subspaces for neural networks nonlinear least squares problems. In particular, the linear conjugate gradient (CG) method works as the inner iterative algorithm for solving the linearized Gauss-Newton normal equation, whereas the outer nonlinear algor...

The dogleg method is a classical trust-region technique for globalizing Newton’s method. While it is widely used in optimization, including large-scale optimization via truncatedNewton approaches, its implementation in general inexact Newton methods for systems of nonlinear equations can be problematic. In this paper, we first outline a very general dogleg method suitable for the general inexac...

Nonlinear least squares (NLS) problems arise in many applications. The common solvers require to compute and store the corresponding Jacobian matrix explicitly, which is too expensive for large problems. In this paper, we propose an effective Jacobian free method especially for large NLS problems because of the novel combination of using automatic differentiation for J(x)v and J (x)v along with...

The minimization of total wire length is one of the most key issue in VLSI physical design automation, as it reduces the cost of physical wiring required along with the electrical hazards of having long wires in the interconnection, power consumption, and signal propagation delay. So, it is still important as cost as well as high performance issue. The problem of reduced wire length routing sol...

In this paper we consider several algorithms for reducing the storage when using a quasi-Newton method in a dogleg–trust region setting for minimizing functions of many variables. Secant methods require O(n2) locations to store an approximate Hessian and O(n2) operations per iteration when minimizing a function of n variables. This storage requirement becomes impractical when n becomes large. O...

We focus on the numerical solution of medium scale bound-constrained systems of nonlinear equations. In this context, we consider an affinescaling trust region approach that allows a great flexibility in choosing the scaling matrix used to handle the bounds. The method is based on a dogleg procedure tailored for constrained problems and so, it is named Constrained Dogleg method. It generates on...

We focus on the numerical solution of medium scale bound-constrained systems of nonlinear equations. In this context, we consider an affinescaling trust region approach that allows a great flexibility in choosing the scaling matrix used to handle the bounds. The method is based on a dogleg procedure tailored for constrained problems and so, it is named Constrained Dogleg method. It generates on...

We report the first successful attempt to generate ultrashort (1-10 ps) relativistic electron bunches characterized by a ramped longitudinal current profile that rises linearly from head to tail and then falls sharply to zero. Bunches with this type of longitudinal shape may be applied to plasma-based accelerator schemes as an optimized drive beam, and to free-electron lasers as a means of redu...