Global Optimization by Annealing Type of Random Tunneling Algorithm
نویسندگان
چکیده
منابع مشابه
A fast annealing evolutionary algorithm for global optimization
By combining the aspect of population in genetic algorithms (GAs) and the simulated annealing algorithm (SAA), a novel algorithm, called fast annealing evolutionary algorithm (FAEA), is proposed. The algorithm is similar to the annealing evolutionary algorithm (AEA), and a very fast annealing technique is adopted for the annealing procedure. By an application of the algorithm to the optimizatio...
متن کاملMetropolis-type Annealing Algorithms for Global Optimization in IRd
We establish the convergence of a class of Metropolis-type Markov chain annealing algorithms for global optimization of a smooth function U(.) on Rd. No prior information is assumed as to what bounded region contains a global minimum. Our analysis is based on writing the Metropolis-type algorithm in the form of a recursive stochastic algorithm Xk+l = Xk ak(VU(Xk) + Jk) + bkWk, where {Wk} are in...
متن کاملSimulated Annealing and Global Optimization
Nelder-Mead (when you don’t know ∇f ) and steepest descent/conjugate gradient (when you do). Both of these methods are based on attempting to generate a sequence of positions xk with monotonically decreasing f(xk) in the hopes that the xk → x∗, the global minimum for f . If f is a convex function (this happens surprisingly often), and has only one local minimum, these methods are exactly the ri...
متن کاملGlobal optimization and simulated annealing
In this paper we are concerned with global optimization, which can be defined as the problem of finding points on a bounded subset of N" in which some real valued function f assumes its optimal (maximal or minimal) value. We present a stochastic approach which is based on the simulated annealing algorithm. The approach closely follows the formulation of the simulated annealing algorithm as orig...
متن کاملGlobal optimization and simulated annealing
In this paper we are concerned with global optimization, which can be defined as the problem of finding points on a bounded subset of IRn in which some real valued functionf assumes its optimal (i.e. maximal or minimal) value. We present a stochastic approach which is based on the simulated annealing algorithm. The approach closely follows the formulation of the simulated annealing algorithm as...
متن کاملذخیره 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: Transactions of the Society of Instrument and Control Engineers
سال: 1993
ISSN: 0453-4654
DOI: 10.9746/sicetr1965.29.1342