Informatica

Difference methods in velocity-pressure variables having a number of important properties are constructed and investigated in this paper for a two-dimensional Navier-Stokes equation. Power neutral approximations of convective members and pressure gradients ensure a conservativity and absolute stability of the proposed algorithms. Their stability and convergence are investigated. The existence and uniqueness of velocity components and pressure gradients is proved.

This paper is devoted to the investigation of difference schemes for the solution of an important free-surface problem: modelling of a liquid-metal contact. The existence of a solution and the convergence of proposed iterative processes are investigated in a weak sense, using the alternative form of the problem as a nonlinear constrained minimization problem.

Finite-difference algorithm for solving convection-diffusion equation with small coefficient at Laplace operator is developed. It is based on equivalent partial differential equation approach. Both linear and nonlinear equations are considered and appropriate finite-difference schemes are proposed. Some analysis of their properties is conducted. The computational efficiency of this algorithm is studied using various test problems. Some results on numerical simulation of capillary isotachophoresis is presented.

A random walk dan be used to model various types of discrete random processes. It may be of interest at some point to find the peak of this function. A direct method of doing so involves evaluating the function at every point and recording the highest value. However, it may be desirable to find the peak without having, to evaluate the function at every point. A search technique was developed to find the peak of a random walk with a minimal number of function evaluations using probabilistic means to guess at where the peak will most likely occur given the parameters of a specific function. A computer program was written to implement the search strategy and a series-of random walk functions of varying lengths were generated to test its performance. Data was compiled and the results show that the search is capable of finding the peak with a significant reduction in the number of function evaluations needed for a point by point search, especially for functions of greater walk length.

In this paper, we present two heuristics for solving the unconstrained quadratic 0–1 programming problem. First heuristic realizes the steepest ascent from the centre of the hypercube, while the second constructs a series of solutions and chooses the best of them. In order to evaluate their worst-case behaviour We define the performance ratio K which uses the objective function value at the reference point x=1/2. We show for both heuristics that K is bounded by 1 from above and this bound is sharp. Finally, we report on the results of a computational study with proposed and local improvement heuristics.

The Freudian psychoanalysis in its modern form assumes that activities of a patient depend on his physical and mental state (“energy”), and result in maintaining his life, in useless waste of his energy (“symptoms”), and in (“useful”) contribution to the society and to patient's energy level.

The problem we are dealing with is following. There exist certain number of nodes η, transmitting messages at random time moments. If time interval between messages transmitted by different nodes are less than some given value, a collision occurs. We can fix the collision, but we cannot determine the nodes engaged in the collision. The hierarchical decomposition of the nodes is used to resolve the collision. At every hierarchical level, a subset of nodes “suspected” as participating in the collision is divided in a certain number of groups. There is a time period given to every group, at which messages can be transmitted. This proceeds while no more collisions occurs. This paper covers the problems of selecting a number of groups, to minimize the longest collision resolution time, as well as average collision resolution time.

The results of investigation of the resource management in radar search are presented in the paper. The time for search of manoeuvring targets is minimized by optimal distribution of radar power among the space directions and by optimization of search parameters.

In some recent papers a discussion on global minimization algorithms for a broad class of functions was started. An idea is presented here why such a case is different from a case of Lipshitzian functions in respect with the convergence and why for a broad class of functions an algorithm converges to global minimum of an objective function if it generates an everywhere dense sequence of trial points.