# Category Archives: Problem-oriented management system

MATHEMATICAL MODEL OF THE PROCESS OF AVERAGING THE PROPERTIES OF BULK MATERIALS AT THEIR EXPIRATION

UDC 004.942
DOI:10.26102/2310-6018/2020.29.2.024

K.A. Melekhina, P.P. Anan’ev, A.V. Plotnikova, S.A. Shestak

The goal is to predict the properties of bulk material flowing from the hopper device. The relevance of the study is due to the lack of input data for controlling the averaging process at processing plants. In this regard, this article is aimed at identifying the transfer function of the hopper device, and the delay time between the feed and the expiration of the material, which will allow you to predict the property of the bulk material, and therefore get the initial data for the averaging process, which is not always available. This article presents an analysis of the existing flow modes of bulk materials when they flow out of a hopper device with one or more holes, the equations describing the transfer function of the hopper device, as well as the time delay between the layer feed and its expiration, are derived. Based on these equations, a mathematical model for controlling the averaging process was constructed, which relates the relative fluctuations and frequency of change in the properties of the ore material entering the hopper. The compiled mathematical model provides reserves for reducing relative fluctuations in the factory. The materials of the article are of practical value for managing the process of averaging ore material at processing plants.

Keywords:mathematic modeling, transfer-function coefficient, averaging out of behavior, granular material, fluxion.

Full text:
MelekhinaSoavtors_2_20_1.pdf

COORDINATION ALGORITHMS FOR MANAGING LARGE-SCALE PROJECTS

UDC 681.3
DOI:10.26102/2310-6018/2020.29.2.028

D.E. Orlova,V.A. Chertov, S.I. Sigarev, S.S. Kochedykov

The article solves the problem of developing two coordination algorithms for managing large-scale projects. The first algorithm is designed to select the appropriate method of coordination when managing the projects under consideration. The algorithm is based on the thesis that the higher the threat of failure of the project plan, the higher the degree of centralization of project management should be, and the lower the threat, the less centralized the project management should be. With this approach, choosing the appropriate method of coordination actually comes down to assessing the threat level. Given that the concept of “level” is of a qualitative nature, it is proposed to characterize it by the function of belonging to gradations: “very high”, “high”, “medium”,” low”, and” zero”, and to evaluate the current threat level, use the measure of hemming proximity, which uses the zero threat level as a reference. The second algorithm is designed to select optimal coordinating solutions based on the criterion of minimum deviation of the project from the specified target state. Its novelty and originality lies in the fact that, unlike the usual optimization approach, it is built on a combination of methods of full iteration and linear programming. This made it possible to correctly take into account the fact that coordinating and design solutions are inextricably linked with each other.

Keywords:project, coordination, project Manager, project performer, membership function, algorithm

Full text:
OrlovaSoavtors_2_20_1.pdf

IDENTIFICATION OF THE RAMSAY LOGISTIC CURVE BY TOTAL LEAST SQUARES

UDC 519.254.1
DOI:10.26102/2310-6018/2020.29.2.019

D.V. Ivanov

Logistics curves are widely used in various fields of economics, technology, biology, chemistry. Estimating the parameters of logistic trends from the results of observations of the dynamic process in the economic system, with the aim of reliable analysis of economic indicators and predicting their future behavior, is one of the main tasks in the economy. One of the logistic models is the Ramsay function. The advantage of this function is the ability to use a linear difference equation to estimate its parameters. At the same time, non-linear data transformations are not required as for the logistics functions of Ferhulst or Gompertz. Modifications of a two-stage estimation algorithm based on the total least squares method and the extended instrumental variables method are proposed for estimating the parameters of the Ramsey curve.Tests have shown that the accuracy of parameter estimation using the proposed modifications is higher than the accuracy of the estimate obtained using the ordinary least squares method (LS).

Keywords:total least square, logistic curve, Ramsay function, estimation of parameters.

Full text:
Ivanov_2_20_1.pdf

MODELS FOR DEFINING CONTROL MOMENTS IN MULTI-LEVEL ORGANIZATIONAL SYSTEMS

UDC 65.012
DOI:10.26102/2310-6018/2020.29.2.003

A.V. Potudinsky, A.P. Preobrazhensky

Process control in organizational systems is an activity aimed at fulfilling tasks (plans, fulfilling orders) throughout the list of system processes. To accomplish this task, management must timely evaluate the implementation of the program, monitor the tendency of performers to deviate from the planned norm and direct the resources at its disposal to eliminate these deviations. In many areas, the calculation of the number of intermediate and final results is automated, and staff can at any time know the numbers that characterize the progress. However, in areas such as construction, high technology and some others, it is rather difficult to evaluate how the program is implemented. Each operation to show the actual implementation of the program and control the timing of each type of result requires full monitoring. This is an expensive operation, often requiring a suspension of the process. Therefore, it is desirable that this be done as rarely as possible, but at the same time, the moment should not be missed when the tendency to deviation will develop into a threat to the program. The process of managing the work of an organizational system of a single-purpose type is considered, the volume of the program of which is expressed as a general equivalent – in units of output (tasks) or in cost. For programs that solve several important types of tasks, it is necessary to simultaneously monitor each type of task.

Keywords:control moment, organizational systems, program execution, modeling, single-purpose type.

Full text:
PotudinskyPreobrazhensky_2_20_1.pdf

MATHEMATICAL AND SIMULATION MODELING OF A CLOSED DISTRIBUTED REGISTRY WITH A CONTROL NODE

UDC 004.942
DOI:10.26102/2310-6018/2020.29.2.001

V.A. Evsin, S.N. Shirobokova, S.P. Vorobyov, V.A. Evsina

Keywords:distributed registry, DLT system, consensus algorithm, mathematical modeling, infinitesimal matrix, Queuing theory, queue theory, simulation modeling.

Full text:
EvsinSoavtors_2_20_1.pdf

COMPARISON OF THE ACCURACY OF EXPERIMENTAL DATA APPROXIMATION USING THE LEAST RELATIVE SQUARES METHOD WITH THE LEAST SQUARES METHOD

UDC 678.04
DOI:10.26102/2310-6018/2020.28.1.042

A.B. Golovanchikov, M.K Doan, A.B. Petrukhin, N.A. Merentsov

The results of comparing the accuracy of approximation of experimental or tabular data obtained using the standard method of least squares (LSM) and the proposed method of least relative squares (LRSM), for example, a given table dependence of the viscosity of a water-glycerine solution on the mass concentration of glycerol. The advantage of the latter is shown as the sum and average values of the local relative deviation of calculated data of viscosity of the desired solution obtained by LRSM, with similar data obtained by standard LSM and maximum values of these relative deviations. So, calculated using LSM average relative deviations of theoretical viscosity of an aqueous solution of glycerin from the specified table, in absolute value equal to 12.9%; LRSM of 5.8%, i.e., below 2 times. Accordingly the largest relative deviations in the LSM are 17.9%, and LRSM – 10.6 %, that is, reduced by 68%. It is proposed to determine the conditional values of parallel experiments based on the experimental data of the main experiment. To do this, the calculation of conditional numerical values of the i-th parallel experience is determined by the method of piecewise linear approximation of i-1 and i+1 numerical values of the main experience or table data. A correlation analysis is performed to determine the correlation coefficients, reproducibility, adequacy, and significance of the coefficients of the resulting regression equation.

Keywords:linearization, approximation, absolute and relative deviations, LSM and LRSM, correlation coefficient, reproducibility, adequacy, significance.

Full text:
GolovanchikovSoavtors_1_20_2.pdf

SITUATIONAL MODEL OF DECISION-MAKING SYSTEM BASED ON ENVIRONMENTAL MONITORING DATA IN THE CONDITIONS OF URBAN DEVELOPMENT

UDC 519.868
DOI:10.26102/2310-6018/2020.28.1.041

I.G. Ivanova, A.D. Danilov, K.Y. Gusev

The paper presents a model of a decision-making system based on environmental monitoring. Air pollution in modern cities is a very urgent problem that is solved at various levels of management. The largest source of pollution is the road network. However, managing traffic flows within urban areas is an impossible or difficult task because of the existing infrastructure of the city. Therefore, we propose a system that, based on the results of training in existing cities, will form recommendations for the development of urban areas, taking into account the level of air pollution. The paper proposes a fuzzy system for supporting decision-making in the conditions of urban development. The article shows the formation of a knowledge base based on retrospective data to improve the accuracy of forecasting, as well as from the simulation environment for increasing the speed of sensing. Ranked recommendations for reduction of pollution of atmospheric air under conditions of development of urban areas. In the fuzzy situational model, a method is proposed for selecting the closest, equal situation from the knowledge base, taking into account the maximum value of the degree of belonging. The developed models can be used as a means of improving the quality of management and decision-making in the conditions of urban development.

Keywords:decision-making, environmental monitoring, fuzzy systems.

Full text:
IvanovaSoavtori_1_20_1.pdf

TYPOLOGY OF RELATIONSHIPS BETWEEN CONSTRUCTION PROJECT PARTICIPANTS IN THE INTERESTS OF RESOLVING CONFLICTS OF INTEREST BETWEEN THEM

UDC 681.3
DOI:10.26102/2310-6018/2020.28.1.038

S.I. Sigarev, V A. Chertov

A typology of relationships between participants in construction projects is given, aimed at resolving conflicts of interest between them. It differs from the known typologies of “common sense” in two ways. First, it is based on taking into account the formal factors of functional, resource and managerial nature that take place in the process of implementing projects of this type. Secondly, it reflects the main features of modern construction projects, namely: their pronounced economic orientation; the presence of resource, social, environmental, historical, cultural, and other restrictions; the structural complexity of the organization of a team of performers with conflicting relationships between them; a wide range of used construction, communication, fire, environmental, and other technologies. As a result of the study, a scheme is presented that identifies 16 types of possible relationships between participants in construction projects grouped by functional, managerial and resource characteristics. This typology can serve as a starting point for solving the problem of rational organization of construction work in the context of a conflict of interests and has the applied value that opens the way to the construction of mathematical models and computer software for decision support in the search for compromises between conflicting participants in construction projects.

Keywords: construction, project, conflict of interest, relationships, typology, functions, resource, management.

Full text:
SigarevChertov_1_20_1.pdf

NEURAL NETWORK BASED SOLUTION FOR REGRESSION TESTING OPTIMIZATION

UDC 004.054
DOI:10.26102/2310-6018/2020.28.1.032

A.D. Danilov, V.M. Mugatina

Regression testing is important task of retesting software systems after changes in the code of product to ensure that changes do not influence previously implemented functionality. Regression testing is run after a new version of software has been developed. Usually only limited subset of test cases is executed for a new version of software through restricted resources. This shows the problem of selection the most important regression test cases. To cope with limited resources, different regression testing techniques was developed to reduce the number of test cases to be executed. One of these techniques is test case prioritization based on neural network model. Such mechanism can collect data about code changes from Version Control System and use it as inputs for neural network. The outputs for such neural network model are regression tests’ execution results. Groups of regression tests can be united by functionality under the test. Neural network model can be trained on real results during the phase of software developing. Trained neural network can detect the most important test cases for execution after each change in product code. Such technique can be used to guide the focus of the testing efforts.

Keywords: software quality assurance, software verification, artificial neural network, regression testing.

Full text:
DanilovMugatina_1_20_1.pdf

MANAGEMENT OF DISTRIBUTED ENERGY SYSTEMS ON THE BASIS OF OPTIMIZATION METHODS AND EXPERT APPROACHES

UDC 517.977
DOI:10.26102/2310-6018/2020.28.1.031

M.V. Pitolin, Y.P. Preobrazhenskiy

Currently, there is a development of various methods and approaches related to the management of distributed energy systems. Using them requires the collection of a large amount of information. When using rating assessments of the functioning of energy systems, a number of problems arise. In managing the resource efficiency of a distributed energy system, the issue of making a rational decision based on the use of information from two sources is essential: a formalized solution to the problem using optimization modeling and expert evaluation of its results. The need to combine such information is determined by the nature of the multi-criteria choice of resource support in the case of taking into account the set of monitored performance indicators of the distributed energy system in this task. Moreover, in most cases, solving the resource efficiency problem by one criterion reduces to a linear programming problem with continuous or integer variables. This paper shows how the assessment of the effectiveness of distributed energy systems is formed. An optimization model of the problem is developed and procedures for the expert evaluation of managerial decisions are formed. The results of the presented work are useful for managing complex distributed energy systems.

Keywords: distributed energy system, optimization, expert assessment, decision making, system analysis.

Full text:
PitolinPreobrazhenskiyUP_1_20_1.pdf