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We consider the approaches to the construction of methods for solving four-dimensional programming problems for calculating directions for multiple minimizations of smooth functions on a set of a given set of linear equalities. The approach consists of two stages.

At the first stage, the problem of quadratic programming is transformed by a numerically stable direct multiplicative algorithm into an equivalent problem of designing the origin of coordinates on a linear manifold, which defines a new mathematical formulation of the dual quadratic problem. For this, a numerically stable direct multiplicative method for solving systems of linear equations is proposed, taking into account the sparsity of matrices presented in packaged form. The advantage of this approach is to calculate the modified Cholesky factors to construct a substantially positive definite matrix of the system of equations and its solution in the framework of one procedure. And also in the possibility of minimizing the filling of the main rows of multipliers without losing the accuracy of the results, and no changes are made in the position of the next processed row of the matrix, which allows the use of static data storage formats.

At the second stage, the necessary and sufficient optimality conditions in the form of Kuhn–Tucker determine the calculation of the direction of descent — the solution of the dual quadratic problem is reduced to solving a system of linear equations with symmetric positive definite matrix for calculating of Lagrange's coefficients multipliers and to substituting the solution into the formula for calculating the direction of descent.

It is proved that the proposed approach to the calculation of the direction of descent by numerically stable direct multiplicative methods at one iteration requires a cubic law less computation than one iteration compared to the well-known dual method of Gill and Murray. Besides, the proposed method allows the organization of the computational process from any starting point that the user chooses as the initial approximation of the solution.

Variants of the problem of designing the origin of coordinates on a linear manifold, a convex polyhedron and a vertex of a convex polyhedron are presented. Also the relationship and implementation of methods for solving these problems are described.

A model of forest insect population dynamics used to simulate of “forest-insect” interactions and for estimation of possible damages of forest stand by pests. This model represented a population as control system where the input variables characterized the influence of modifier (climatic) factors and the feedback loop describes the effect of regulatory factors (parasites, predators and population interactions). The technique of stress testing on the basis of population dynamics model proposed for assessment of the risks of forest stand damage and destruction after insect impact. The dangerous forest pest pine looper Bupalus piniarius L. considered as the object of analysis. Computer experiments were conducted to assess of outbreak risks with possible climate change in the territory of Central Siberia. Model experiments have shown that risk of insect impact on the forest is not increased significantly in condition of sufficiently moderate warming (not more than 4 °C in summer period). However, a stronger warming in the territory of Central Siberia, combined with a dry summer condition could cause a significant increase in the risk of pine looper outbreaks.

The development of the Splitting Method for Incompressible Fluid flows (SMIF) during last 50 years is described. The hybrid explicit finite difference scheme of method SMIF is based on Modified Central Difference Scheme (MCDS) and Modified Upwind Difference Scheme (MUDS) with special switch condition depending on the velocity sign and the signs of the first and second differences of transferred functions. Application of this method for solving of some tasks (the spatial flow around a sphere and a circular cylinder for homogeneous and stratified fluids in a wide range of dimensionless parameters of the problem, including the transitional regimes (2D–3D transition, laminar-turbulent transition in the boundary layer); a plane problem of fluid flows with a free surface; a dynamics of vortex pair in a water; a collapse of spots in stratified fluid; the air-, heat-, and mass transfer in «clean rooms») is demonstrated.

Newton and quasi-Newton methods of absolute optimization based on Cholesky factorization with adaptive step and finite difference approximation of the first and the second derivatives. In order to raise effectiveness of the quasi-Newton methods a modified version of Cholesky decomposition of quasi-Newton matrix is suggested. It solves the problem of step scaling while descending, allows approximation by non-quadratic functions, and integration with confidential neighborhood method. An approach to raise Newton methods effectiveness with finite difference approximation of the first and second derivatives is offered. The results of numerical research of algorithm effectiveness are shown.

The article reports the findings of an investigation into pollution migration processes at the municipal solid waste (MSW) landfill located in the water protection zone of Lake Seliger (Tver Region). The distribution of pollutants is investigated and migration parameters are determined in field and laboratory conditions at the landfill site. A mathematical model describing physical and chemical processes of substance migration in soil strata is constructed. Pollutant migration is found to be due to a variety of factors. The major ones, having a significant impact on the migration of MSW ingredients and taken into account mathematically, include convective transport, diffusion and sorption processes. A modified mathematical model differs from its conventional counterparts by considering a number of parameters reflecting the decrease in the concentration of ammonium and nitrate nitrogen ions in ground water (transpiration by plant roots, dilution with infiltration waters, etc.). An analytical solution to assess the pollutant spread from the landfill is presented. The mathematical model provides a set of simulation models helping to obtain a computational solution of specific problems, vertical and horizontal migration of substances in the underground flow. Numerical experiments, analytical solutions, as well as field and laboratory data was studied the dynamics of pollutant distribution in the object under study up to the lake. A long-term forecast for the spread of landfill pollution is made. Simulation experiments showed that some zones of clean groundwater interact with those of contaminated groundwater during the pollution migration from the landfill, each characterized by a different pollutant content. The data of a computational experiments and analytical calculations are consistent with the findings of field and laboratory investigations of the object and give grounds to recommend the proposed models for predicting pollution migration from a landfill. The analysis of the pollution migration simulation allows to substantiate the numerical estimates of the increase in $NH_4^+$ and $NO_3^-$ ion concentration with the landfill operation time. It is found that, after 100 years following the landfill opening, toxic filtrate components will fill the entire pore space from the landfill to the lake resulting in a significant deterioration of the ecosystem of Lake Seliger.

Metal hydrides are an interesting class of chemical compounds that can reversibly bind a large amount of hydrogen and are, therefore, of interest for energy applications. Understanding the factors affecting the kinetics of hydride formation and decomposition is especially important. Features of the material, experimental setup and conditions affect the mathematical description of the processes, which can undergo significant changes during the processing of experimental data. The article proposes a general approach to numerical modeling of the formation and decomposition of metal hydrides and solving inverse problems of estimating material parameters from measurement data. The models are divided into two classes: diffusive ones, that take into account the gradient of hydrogen concentration in the metal lattice, and models with fast diffusion. The former are more complex and take the form of non-classical boundary value problems of parabolic type. A rather general approach to the grid solution of such problems is described. The second ones are solved relatively simply, but can change greatly when model assumptions change. Our experience in processing experimental data shows that a flexible software tool is needed; a tool that allows, on the one hand, building models from standard blocks, freely changing them if necessary, and, on the other hand, avoiding the implementation of routine algorithms. It also should be adapted for high-performance systems of different paradigms. These conditions are satisfied by the HIMICOS library presented in the paper, which has been tested on a large number of experimental data. It allows simulating the kinetics of formation and decomposition of metal hydrides, as well as related tasks, at three levels of abstraction. At the low level, the user defines the interface procedures, such as calculating the time layer based on the previous layer or the entire history, calculating the observed value and the independent variable from the task variables, comparing the curve with the reference. Special algorithms can be used for solving quite general parabolic-type boundary value problems with free boundaries and with various quasilinear (i.e., linear with respect to the derivative only) boundary conditions, as well as calculating the distance between the curves in different metric spaces and with different normalization. This is the middle level of abstraction. At the high level, it is enough to choose a ready tested model for a particular material and modify it in relation to the experimental conditions.

Technological development determines the emergence of highly detailed data in time and space, which expands the possibilities of analysis, allowing us to consider consumer decisions and the competitive behavior of enterprises in all their diversity, taking into account the context of the territory and the characteristics of time periods. Despite the promise of such studies, they are currently limited in the scientific literature. This is due to the range of problems, the solution of which is considered in this paper. The article draws attention to the complexity of the analysis of depersonalized high-frequency data and the possibility of modeling consumption changes in time and space based on them. The features of the new type of data are considered on the example of real depersonalized data received from the fiscal data operator “First OFD” (JSC “Energy Systems and Communications”). It is shown that along with the spectrum of problems inherent in high-frequency data, there are disadvantages associated with the process of generating data on the side of the sellers, which requires a wider use of data mining tools. A series of statistical tests were carried out on the data under consideration, including a Unit-Root Test, test for unobserved individual effects, test for serial correlation and for cross-sectional dependence in panels, etc. The presence of spatial autocorrelation of the data was tested using modified tests of Lagrange multipliers. The tests carried out showed the presence of a consistent correlation and spatial dependence of the data, which determine the expediency of applying the methods of panel and spatial analysis in relation to high-frequency data accumulated by fiscal operators. The constructed models made it possible to substantiate the spatial relationship of sales growth and its dependence on the day of the week. The limitation for increasing the predictive ability of the constructed models and their subsequent complication, due to the inclusion of explanatory factors, was the lack of open access statistics grouped in the required detail in time and space, which determines the relevance of the formation of high-frequency geographically structured data bases.