Cutting angle methods in global optimization

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Cutting angle method - a tool for constrained global optimization

Cutting angle method (CAM) is a deterministic global optimization technique applicable to Lipschitz functions f : Rn → R. The method builds a sequence of piecewise linear lower approximations to the objective function f . The sequence of solutions to these relaxed problems converges to the global minimum of f . This article adapts CAM to the case of linear constraints on the feasible domain. We...

متن کامل

Trajectory Methods in Global Optimization

We review the application of trajectory methods (not including homotopy methods) to global optimization problems. The main ideas and the most successful methods are described and directions of current and future research are indicated.

متن کامل

Homotopy Optimization Methods for Global Optimization

We define a new method for global optimization, the Homotopy Optimization Method (HOM). This method differs from previous homotopy and continuation methods in that its aim is to find a minimizer for each of a set of values of the homotopy parameter, rather than to follow a path of minimizers. We define a second method, called HOPE, by allowing HOM to follow an ensemble of points obtained by per...

متن کامل

Trajectory Optimization Using Global Methods

This paper compares three different global indirect approaches for solving the problem of finding optimal trajectories for low thrust spacecraft. The three methods tested were downhill simplex, genetic algorithms and simulated annealing. Two problems are analyzed. The first is a planar low thrust problem. This is the problem of finding a minimum time trajectory from Earth to Mars orbit using a ...

متن کامل

Advances in Global Optimization: Methods and Applications

Semi-deteministic optimization methods We consider with : J Ω → Ω ⊂. We make the following assump tions: 1 (,) J C ∈ Ω and is coercive. The infimum of J is denoted by J m (when J m is unknown, we set J m to a low value). Many deterministic minimization algorithms can be seen as discrete dynamical systems coming from the discretization of first or second order Cauchy problems. On the other hand,...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Applied Mathematics Letters

سال: 1999

ISSN: 0893-9659

DOI: 10.1016/s0893-9659(98)00179-7