Optimization methods based on iterative schemes can be divided into two classes: linesearch methods and trustregion methods. While linesearch techniques are commonly found in various vision applications, not much attention is paid to trust-region methods. Motivated by the fact that linesearch methods can be considered as special cases of trust-region methods, we propose to apply trust-region me...

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...

This paper presents a simple but eecient way to nd a good initial trust region radius in trust region methods for nonlinear optimization. The method consists of monitoring the agreement between the model and the objective function along the steepest descent direction, computed at the starting point. Further improvements for the starting point are also derived from the information gleaned during...

In this paper, we present a new trust region method for unconstrained nonlinear programming in which we blend adaptive trust region algorithm by non-monotone strategy to propose a new non-monotone trust region algorithm with automatically adjusted radius. Both non-monotone strategy and adaptive technique can help us introduce a new algorithm that reduces the number of iterations and function ev...

We present a trust region method for minimizing a general diierentiable function restricted to an arbitrary closed set. We prove a global convergence theorem. The trust region method deenes diicult subproblems that are solvable in some particular cases. We analyze in detail the case where the domain is an Euclidean ball. For this case we present numerical experiments where we consider diierent ...

Trust region method for a class of large-scale minimization problems, the unconstrained discrete-time optimal control (DTOC) problems, is considered. Although the trust region algorithms developed in 4] and 13] are very economical they lack the ability to handle the so-called hard case. In this paper, We show that the trust region subproblem can be solved within an acceptable accuracy without f...

In this paper, we present a nonmonotone adaptive trust region method for unconstrained optimization based on conic model. The new method combines nonmonotone technique and a new way to determine trust region radius at each iteration. The local and global convergence properties are proved under reasonable assumptions. Numerical experiments show that our algorithm is effective.

In this paper we develop a trust region algorithm for constrained parabolic boundary control problems. The method is a projected form of the Steihaug trust-region-CG method with a smoothing step added at each iteration to improve performance in the global phase and provide mesh-independent sup-norm convergence in the terminal phase.

Transition to superlinear local convergence is shown for a modified version of the trust-region filter-SQP method for nonlinear programming introduced by Fletcher, Leyffer, and Toint [8]. Hereby, the original trust-region SQP-steps can be used without an additional second order correction. The main modification consists in using the Lagrangian function value instead of the objective function va...