This article presents the results of the adaptation algorithm for searching the global minimum of multiextreme criterion function of great count of variables with constraints based on the method of simulated annealing algorithm for systems of parallel and distributed computing. The reliability of the searching global minimum, depending on the number of nodes of parallel computer system is investigated. Distributed simulated annealing algorithm using the scheme of quenching, created by Boltzmann allows to search out the area of the global minimum for a short time is represented.
In the paper we consider the cardinality constrained portfolio optimization problem. Constraint on the number of assets in portfolio leads to the mixed integer optimization problem. Effective frontier is constructed using the metaheuristic approach by genetic algorithm.
In the paper we develop metaheuristic method based on differential evolution for finding efficient frontier in solving the portfolio optimisation problem for investor with non concave utility function which reflects asymmetric investor attitude to losses and gains.
In this paper we propose the algorithm for finding weights of feedforward artificial neural networks with one hidden layer to approximate polynomial functions and its derivatives with a given error. We use the rational sigmoidal function as a transfer function.
The object of study is the dynamic system defined by geometrical images of automata. The phase space of the system is determined by orthogonal and affine transformations of geometric images. Compositions of dynamical systems of a given type and their characteristics are studied.
The concept of a generalized diagnostic experiment for fuzzy automata is introduced. A method constructing diagnostic experiments for fuzzy automata is proposed. The method is based on diagnostic tree structure. It is establish that the problem of diagnostic experiment synthesis is a multi-criteria optimization problem.
