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The article substantiates the need to develop and analyze mathematical models that take into account the mutual influence of long (Kondratiev) waves of economic development. The analysis of the available publications shows that at the model level, the direct and inverse relationships between intersecting long waves are still insufficiently studied. As practice shows, the production of the current long wave can receive an additional impetus for growth from the technologies of the next long wave. The technologies of the next industrial revolution often serve as improving innovations for the industries born of the previous industrial revolution. As a result, the new long wave increases the amplitude of the oscillations of the trajectory of the previous long wave. Such results of the interaction of long waves in the economy are similar to the effects of interference of physical waves. The mutual influence of the recessions and booms of the economies of different countries gives even more grounds for comparing the consequences of this mutual influence with the interference of physical waves. The article presents a model for the development of the technological base of production, taking into account the possibilities of combining old and new technologies. The model consists of several sub-models. The use of a different mathematical description for the individual stages of updating the technological base of production allows us to take into account the significant differences between the successive phases of the life cycle of general purpose technologies, considered in modern literature as the technological basis of industrial revolutions. One of these phases is the period of formation of the appropriate infrastructure necessary for the intensive diffusion of new general purpose technology, for the rapid development of industries using this technology. The model is used for illustrative calculations with the values of exogenous parameters corresponding to the logic of changing long waves. Despite all the conditionality of the illustrative calculations, the configuration of the curve representing the change in the return on capital in the simulated period is close to the configuration of the real trajectory of the return on private fixed assets of the US economy in the period 1982-2019. The factors that remained outside the scope of the presented model, but which are advisable to take into account when describing the interference of long waves of economic development, are indicated.

The article presents the numerical modeling and study of the kinetic model of propane pyrolysis. The study of the reaction kinetics is a necessary stage in modeling the dynamics of the gas flow in the reactor.

The kinetic model of propane pyrolysis is a nonlinear system of ordinary differential equations of the first order with parameters, the role of which is played by the reaction rate constants. Math modeling of processes is based on the use of the mass conservation law. To solve an initial (forward) problem, implicit methods for solving stiff ordinary differential equation systems are used. The model contains 60 input kinetic parameters and 17 output parameters corresponding to the reaction substances, of which only 9 are observable. In the process of solving the problem of estimating parameters (inverse problem), there is a question of non-uniqueness of the set of parameters that satisfy the experimental data. Therefore, before solving the inverse problem, the possibility of determining the parameters of the model is analyzed (analysis of identifiability).

To analyze identifiability, we use the orthogonal method, which has proven itself well for analyzing models with a large number of parameters. The algorithm is based on the analysis of the sensitivity matrix by the methods of differential and linear algebra, which shows the degree of dependence of the unknown parameters of the models on the given measurements. The analysis of sensitivity and identifiability showed that the parameters of the model are stably determined from a given set of experimental data. The article presents a list of model parameters from most to least identifiable. Taking into account the analysis of the identifiability of the mathematical model, restrictions were introduced on the search for less identifiable parameters when solving the inverse problem.

The inverse problem of estimating the parameters was solved using a genetic algorithm. The article presents the found optimal values of the kinetic parameters. A comparison of the experimental and calculated dependences of the concentrations of propane, main and by-products of the reaction on temperature for different flow rates of the mixture is presented. The conclusion about the adequacy of the constructed mathematical model is made on the basis of the correspondence of the results obtained to physicochemical laws and experimental data.

The work is devoted to the study of subgradient methods with different variations of the Polyak stepsize for minimization functions from the class of weakly convex and relatively weakly convex functions that have the corresponding analogue of a sharp minimum. It turns out that, under certain assumptions about the starting point, such an approach can make it possible to justify the convergence of the subgradient method with the speed of a geometric progression. For the subgradient method with the Polyak stepsize, a refined estimate for the rate of convergence is proved for minimization problems for weakly convex functions with a sharp minimum. The feature of this estimate is an additional consideration of the decrease of the distance from the current point of the method to the set of solutions with the increase in the number of iterations. The results of numerical experiments for the phase reconstruction problem (which is weakly convex and has a sharp minimum) are presented, demonstrating the effectiveness of the proposed approach to estimating the rate of convergence compared to the known one. Next, we propose a variation of the subgradient method with switching over productive and non-productive steps for weakly convex problems with inequality constraints and obtain the corresponding analog of the result on convergence with the rate of geometric progression. For the subgradient method with the corresponding variation of the Polyak stepsize on the class of relatively Lipschitz and relatively weakly convex functions with a relative analogue of a sharp minimum, it was obtained conditions that guarantee the convergence of such a subgradient method at the rate of a geometric progression. Finally, a theoretical result is obtained that describes the influence of the error of the information about the (sub)gradient available by the subgradient method and the objective function on the estimation of the quality of the obtained approximate solution. It is proved that for a sufficiently small error $\delta > 0$, one can guarantee that the accuracy of the solution is comparable to $\delta$.

In this article a method of legacy information systems handling is offered. During professional activities of specialists of various domains of industry they face with the problem that computer software that was involved in product development stage becomes obsolete much quickly than the product itself. At the same time switch to any modern software might be not possible due to various reasons. This problem is known as "legacy system" problem. It appears when product lifecycle is sufficiently longer than that of software systems that were used for product creation. In this article author offers an approach for solving this problem along with computer application based on this approach.

This article presents an integrated dynamic model of eco-economic system of the Republic of Armenia (RA). This model is constructed using system dynamics methods, which allow to consider the major feedback related to key characteristics of eco-economic system. Such model is a two-objective optimization problem where as target functions the level of air pollution and gross profit of national economy are considered. The air pollution is minimized due to modernization of stationary and mobile sources of pollution at simultaneous maximization of gross profit of national economy. At the same time considered eco-economic system is characterized by the presence of internal constraints that must be accounted at acceptance of strategic decisions. As a result, we proposed a systematic approach that allows forming sustainable solutions for the development of the production sector of RA while minimizing the impact on the environment. With the proposed approach, in particular, we can form a plan for optimal enterprise modernization and predict long-term dynamics of harmful emissions into the atmosphere.

This paper targets programmers and developers interested in utilizing parallel programming techniques to enhance application performance. The Oracle Solaris Studio software provides state-of-the-art optimizing and parallelizing compilers for C, C++ and Fortran, an advanced debugger, and optimized mathematical and performance libraries. Also included are an extremely powerful performance analysis tool for profiling serial and parallel applications, a thread analysis tool to detect data races and deadlock in memory parallel programs, and an Integrated Development Environment (IDE). The Oracle Message Passing Toolkit software provides the high-performance MPI libraries and associated run-time environment needed for message passing applications that can run on a single system or across multiple compute systems connected with high performance networking, including Gigabit Ethernet, 10 Gigabit Ethernet, InfiniBand and Myrinet. Examples of OpenMP and MPI are provided throughout the paper, including their usage via the Oracle Solaris Studio and Oracle Message Passing Toolkit products for development and deployment of both serial and parallel applications on SPARC and x86/x64 based systems. Throughout this paper it is demonstrated how to develop and deploy an application parallelized with OpenMP and/or MPI.

We show that basic properties of some models of monopolistic competition are described using families of hypergeometric functions. The results obtained by building a general equilibrium model in a multisector economy producing a differentiated good in $n$ high-tech sectors in which single-product firms compete monopolistically using the same technology. Homogeneous (traditional) sector is characterized by perfect competition. Workers are motivated to find a job in high-tech sectors as wages are higher there. However, they are at risk to remain unemployed. Unemployment persists in equilibrium by labor market imperfections. Wages are set by firms in high-tech sectors as a result of negotiations with employees. It is assumed that individuals are homogeneous consumers with identical preferences that are given the separable utility function of general form. In the paper the conditions are found such that the general equilibrium in the model exists and is unique. The conditions are formulated in terms of the elasticity of substitution $\mathfrak{S}$ between varieties of the differentiated good which is averaged over all consumers. The equilibrium found is symmetrical with respect to the varieties of differentiated good. The equilibrium variables can be represented as implicit functions which properties are associated elasticity $\mathfrak{S}$ introduced by the authors. A complete analytical description of the equilibrium variables is possible for known special cases of the utility function of consumers, for example, in the case of degree functions, which are incorrect to describe the response of the economy to changes in the size of the markets. To simplify the implicit function, we introduce a utility function defined by two one-parameter families of hypergeometric functions. One of the families describes the pro-competitive, and the other — anti-competitive response of prices to an increase in the size of the economy. A parameter change of each of the families corresponds to all possible values of the elasticity $\mathfrak{S}$. In this sense, the hypergeometric function exhaust natural utility function. It is established that with the increase in the elasticity of substitution between the varieties of the differentiated good the difference between the high-tech and homogeneous sectors is erased. It is shown that in the case of large size of the economy in equilibrium individuals consume a small amount of each product as in the case of degree preferences. This fact allows to approximate the hypergeometric functions by the sum of degree functions in a neighborhood of the equilibrium values of the argument. Thus, the change of degree utility functions by hypergeometric ones approximated by the sum of two power functions, on the one hand, retains all the ability to configure parameters and, on the other hand, allows to describe the effects of change the size of the sectors of the economy.

Optimal management of fuel supply system boils down to choosing an energy development strategy which provides consumers with the most efficient and reliable fuel and energy supply. As a part of the program on switching the heat supply distributed management system of the Udmurt Republic to renewable energy sources, an “Information-analytical system of regional alternative fuel supply management” was developed. The paper presents the mathematical model of optimal management of fuel supply logistic system consisting of three interconnected levels: raw material accumulation points, fuel preparation points and fuel consumption points, which are heat sources. In order to increase effective the performance of regional fuel supply system a modification of information-analytical system and extension of its set of functions using the methods of quick responding when emergency occurs are required. Emergencies which occur on any one of these levels demand the management of the whole system to reconfigure. The paper demonstrates models and algorithms of optimal management in case of emergency involving break down of such production links of logistic system as raw material accumulation points and fuel preparation points. In mathematical models, the target criterion is minimization of costs associated with the functioning of logistic system in case of emergency. The implementation of the developed algorithms is based on the usage of genetic optimization algorithms, which made it possible to obtain a more accurate solution in less time. The developed models and algorithms are integrated into the information-analytical system that enables to provide effective management of alternative fuel supply of the Udmurt Republic in case of emergency.

Simulation of combat and military operations is the most important scientific and practical task aimed at providing the command of quantitative bases for decision-making. The first models of combat were developed during the First World War (M. Osipov, F. Lanchester), and now they are widely used in connection with the massive introduction of automation tools. At the same time, the models of combat and war do not fully take into account the moral potentials of the parties to the conflict, which motivates and motivates the further development of models of battle and war. A probabilistic model of combat is considered, in which the parameter of combat superiority is determined through the parameter of moral (the ratio of the percentages of the losses sustained by the parties) and the parameter of technological superiority. To assess the latter, the following is taken into account: command experience (ability to organize coordinated actions), reconnaissance, fire and maneuverability capabilities of the parties and operational (combat) support capabilities. A game-based offensive-defense model has been developed, taking into account the actions of the first and second echelons (reserves) of the parties. The target function of the attackers in the model is the product of the probability of a breakthrough by the first echelon of one of the defense points by the probability of the second echelon of the counterattack repelling the reserve of the defenders. Solved the private task of managing the breakthrough of defense points and found the optimal distribution of combat units between the trains. The share of troops allocated by the parties to the second echelon (reserve) increases with an increase in the value of the aggregate combat superiority parameter of those advancing and decreases with an increase in the value of the combat superiority parameter when repelling a counterattack. When planning a battle (battles, operations) and the distribution of its troops between echelons, it is important to know not the exact number of enemy troops, but their capabilities and capabilities, as well as the degree of preparedness of the defense, which does not contradict the experience of warfare. Depending on the conditions of the situation, the goal of an offensive may be to defeat the enemy, quickly capture an important area in the depth of the enemy’s defense, minimize their losses, etc. For scaling the offensive-defense model for targets, the dependencies of the losses and the onset rate on the initial ratio of the combat potentials of the parties were found. The influence of social costs on the course and outcome of wars is taken into account. A theoretical explanation is given of a loss in a military company with a technologically weak adversary and with a goal of war that is unclear to society. To account for the influence of psychological operations and information wars on the moral potential of individuals, a model of social and information influence was used.

In the presented work, a hybrid optimal simulation model of an assembly shop in the AnyLogic environment has been developed, which allows you to select the parameters of production systems. To build a hybrid model of the investigative approach, discrete-event modeling and aggressive modeling are combined into a single model with an integrating interaction. Within the framework of this work, a mechanism for the development of a production system consisting of several participants-agents is described. An obvious agent corresponds to a class in which a set of agent parameters is specified. In the simulation model, three main groups of operations performed sequentially were taken into account, and the logic for working with rejected sets was determined. The product assembly process is a process that occurs in a multi-phase open-loop system of redundant service with waiting. There are also signs of a closed system — scrap flows for reprocessing. When creating a distribution system in the segment, it is mandatory to use control over the execution of requests in a FIFO queue. For the functional assessment of the production system, the simulation model includes several functional functions that describe the number of finished products, the average time of preparation of products, the number and percentage of rejects, the simulation result for the study, as well as functional variables in which the calculated utilization factors will be used. A series of modeling experiments were carried out in order to study the behavior of the agents of the system in terms of the overall performance indicators of the production system. During the experiment, it was found that the indicator of the average preparation time of the product is greatly influenced by such parameters as: the average speed of the set of products, the average time to complete operations. At a given limitation interval, we managed to select a set of parameters that managed to achieve the largest possible operation of the assembly line. This experiment implements the basic principle of agent-based modeling — decentralized agents make a personal contribution and affect the operation of the entire simulated system as a whole. As a result of the experiments, thanks to the selection of a large set of parameters, it was possible to achieve high performance indicators of the assembly shop, namely: to increase the productivity indicator by 60%; reduce the average assembly time of products by 38%.