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This paper presents a universal method for constructing an agent-based model of complex systems for their further clear computer representation by means of object-oriented programming languages. The method specifies both steps of model developing from the mathematical description of the system to the determined architecture of the program simulating the system. The efficiency of the method is illustrated by the construction of the two simulation models for the complex systems of various origins: the interactive simulation of the stock exchange and space-time simulation of biological species competition.

In this paper we consider one of the core subsystems of the retail payment system named “Developer”. The Queuing System for modeling this subsystem was developed and information about it is provided. The task for the assignment problem was set up and solved (the modification of the Hungarian algorithm was used). Information about Agent Based Model for subsystem “Developer” and the results of the simulation experiments are given.

In this study we discuss methods to solve optimal control problems based on neural network techniques. We study hierarchical dynamical two-level system for surface water quality control. The system consists of a supervisor (government) and a few agents (enterprises). We consider this problem from the point of agents. In this case we solve optimal control problem with constraints. To solve this problem, we use Pontryagin’s maximum principle, with which we obtain optimality conditions. To solve emerging ODEs, we use feedforward neural network. We provide a review of existing techniques to study such problems and a review of neural network’s training methods. To estimate the error of numerical solution, we propose to use defect analysis method, adapted for neural networks. This allows one to get quantitative error estimations of numerical solution. We provide examples of our method’s usage for solving synthetic problem and a surface water quality control model. We compare the results of this examples with known solution (when provided) and the results of shooting method. In all cases the errors, estimated by our method are of the same order as the errors compared with known solution. Moreover, we study surface water quality control problem when no solutions is provided by other methods. This happens because of relatively large time interval and/or the case of several agents. In the latter case we seek Nash equilibrium between agents. Thus, in this study we show the ability of neural networks to solve various problems including optimal control problems and differential games and we show the ability of quantitative estimation of an error. From the numerical results we conclude that the presence of the supervisor is necessary for achieving the sustainable development.

The gradual incorporation of automated vehicles into the global transport networks leads to the need to develop tools to assess the impact of this process on various aspects of traffic. This implies a more organized movement of automated vehicles which can form uniformly moving platoons. The influence of the formation and movement of these platoons on the dynamics of traffic flow is of great interest. The currently most developed traffic flow models are based on the cellular automaton approach. They are mainly developed in the direction of increasing accuracy. This inevitably leads to the complication of models, which in their modern form have significantly moved away from the original philosophy of cellular automata, which implies simplicity and schematicity of models at the level of evolution rules, leading, however, to a complex organized behavior of the system. In the present paper, a simulation model of connected automated vehicles platoon dynamics in a heterogeneous transport system is proposed, consisting of two types of agents (vehicles): human-driven and automated. The description of the temporal evolution of the system is based on modified rules 184 and 240 for elementary cellular automata. Human-driven vehicles move according to rule 184 with the addition of accidental braking, the probability of which depends on the distance to the vehicle in front. For automated vehicles, a combination of rules is used depending on the type of nearest neighbors, regardless of the distance to them, which brings non-local interaction to the model. At the same time, it is considered that a group of sequentially moving connected automated vehicles can form an organized platoon. The influence of the ratio of types of vehicles in the system on the characteristics of the traffic flow during free movement on a circular one-lane and two-lane roads, as well as in the presence of a traffic light, is studied. The simulation results show that the effect of platoon formation is significant for a freeway traffic flow; the presence of a traffic light reduces the positive effect by about half. The movement of platoons of connected automated vehicles on two-lane roads with the possibility of lane changing was also studied. It is shown that considering the types of neighboring vehicles (automated or human-driven) when changing lanes for automated vehicles has a positive effect on the characteristics of the traffic flow.

This article is dedicated to applicability justification as well as advantages and disadvantages analysis of discrete models in population dynamics. Discretization is the process of transferring continuous functions, models, and equations into discrete counterparts. We consider how temporal, spatial and structural discretization can be applied for solving typical issues in mathematical ecology, and try to estimate corresponding models adequacy and applicability limitations.

One of the promising technologies for enhanced oil recovery in the development of unconventional oil reservoirs is the thermo-gas method. The method is based on the injection of an oxygen-containing mixture into the formation and its transformation into a highly efficient displacing agent miscible with the formation of oil due to spontaneous in-situ oxidative processes. In some cases, this method has great potential compared to other methods of enhanced oil recovery. This paper discusses some issues of the propagation of in-situ combustion waves. Depending on the parameters of the reservoir and the injected mixture, such waves can propagate in different modes. In this paper, only the direct-flow inverse propagation mode is considered. In this mode, the combustion wave propagates in the direction of the oxidant flow and the reaction front lags behind the heatwave, in which the substance (hydrocarbon fractions, porous skeleton, etc.) is heated to temperatures sufficient for the oxidation reaction to occur. The paper presents the results of an analytical study and numerical simulation of the structure of the inverse wave of in-situ combustion. in two-phase flow in a porous layer. Some simplifying assumptions about the thermal properties of fluid phases was accepted, which allow, on the one hand, to modify the in-situ combustion model observable for analysis, and with another is to convey the main features of this process. The solution of the “running wave” type is considered and the conditions of its implementation are specified. Selected two modes of reaction trailing front regime in-situ combustion waves: hydrodynamic and kinetic. Numerical simulation of the in-situ combustion wave propagation was carried out with using the thermohydrodynamical simulator developed for the numerical integration of non-isothermal multicomponent filtration flows accompanied by phase transitions and chemical reaction.

Dynamic game theoretic models of the corporative innovative development are investigated. The proposed models are based on concordance of private and public interests of agents. It is supposed that the structure of interests of each agent includes both private (personal interests) and public (interests of the whole company connected with its innovative development first) components. The agents allocate their personal resources between these two directions. The system dynamics is described by a difference (not differential) equation. The proposed model of innovative development is studied by simulation and the method of enumeration of the domains of feasible controls with a constant step. The main contribution of the paper consists in comparative analysis of efficiency of the methods of hierarchical control (compulsion or impulsion) for information structures of Stackelberg or Germeier (four structures) by means of the indices of system compatibility. The proposed model is a universal one and can be used for a scientifically grounded support of the programs of innovative development of any economic firm. The features of a specific company are considered in the process of model identification (a determination of the specific classes of model functions and numerical values of its parameters) which forms a separate complex problem and requires an analysis of the statistical data and expert estimations. The following assumptions about information rules of the hierarchical game are accepted: all players use open-loop strategies; the leader chooses and reports to the followers some values of administrative (compulsion) or economic (impulsion) control variables which can be only functions of time (Stackelberg games) or depend also on the followers’ controls (Germeier games); given the leader’s strategies all followers simultaneously and independently choose their strategies that gives a Nash equilibrium in the followers’ game. For a finite number of iterations the proposed algorithm of simulation modeling allows to build an approximate solution of the model or to conclude that it doesn’t exist. A reliability and efficiency of the proposed algorithm follow from the properties of the scenario method and the method of a direct ordered enumeration with a constant step. Some comprehensive conclusions about the comparative efficiency of methods of hierarchical control of innovations are received.

The present article describes the authors’ model of construction of the distributed computer network and realization in it of the distributed calculations which are carried out within the limits of the software-information environment providing management of the information, automated and engineering systems of intellectual buildings. The presented model is based on the functional approach with encapsulation of the non-determined calculations and various side effects in monadic calculations that allows to apply all advantages of functional programming to a choice and execution of scenarios of management of various aspects of life activity of buildings and constructions. Besides, the described model can be used together with process of intellectualization of technical and sociotechnical systems for increase of level of independence of decision-making on management of values of parameters of the internal environment of a building, and also for realization of methods of adaptive management, in particular application of various techniques and approaches of an artificial intellect. An important part of the model is a directed acyclic graph, which is an extension of the blockchain with the ability to categorically reduce the cost of transactions taking into account the execution of smart contracts. According to the authors it will allow one to realize new technologies and methods — the distributed register on the basis of the directed acyclic graph, calculation on edge and the hybrid scheme of construction of artificial intellectual systems — and all this together can be used for increase of efficiency of management of intellectual buildings. Actuality of the presented model is based on necessity and importance of translation of processes of management of life cycle of buildings and constructions in paradigm of Industry 4.0 and application for management of methods of an artificial intellect with universal introduction of independent artificial cognitive agents. Model novelty follows from cumulative consideration of the distributed calculations within the limits of the functional approach and hybrid paradigm of construction of artificial intellectual agents for management of intellectual buildings. The work is theoretical. The article will be interesting to scientists and engineers working in the field of automation of technological and industrial processes both within the limits of intellectual buildings, and concerning management of complex technical and social and technical systems as a whole.

The article describes a mathematical model that simulates performance of a hierarchical organization during an early stage of a crisis. A distinguished feature of this stage of crisis is presence of so called early warning signals containing information on the approaching event. Employees are capable of catching the early warnings and of preparing the organization for the crisis based on the signals’ meaning. The efficiency of the preparation depends on both parameters of the organization and parameters of the crisis. The proposed simulation agentbased model is implemented on Java programming language and is used for conducting experiments via Monte- Carlo method. The goal of the experiments is to compare how centralized and decentralized organizational structures perform during sudden and smoldering crises. By centralized organizations we assume structures with high number of hierarchy levels and low number of direct reports of every manager, while decentralized organizations mean structures with low number of hierarchy levels and high number of direct reports of every manager. Sudden crises are distinguished by short early stage and low number of warning signals, while smoldering crises are defined as crises with long lasting early stage and high number of warning signals not necessary containing important information. Efficiency of the organizational performance during early stage of a crisis is measured by two parameters: percentage of early warnings which have been acted upon in order to prepare organization for the crisis, and time spent by top-manager on working with early warnings. As a result, we show that during early stage of smoldering crises centralized organizations process signals more efficiently than decentralized organizations, while decentralized organizations handle early warning signals more efficiently during early stage of sudden crises. However, occupation of top-managers during sudden crises is higher in decentralized organizations and it is higher in centralized organizations during smoldering crises. Thus, neither of the two classes of organizational structures is more efficient by the two parameters simultaneously. Finally, we conduct sensitivity analysis to verify the obtained results.

The number of papers addressing the forecasting of the infectious disease morbidity is rapidly growing due to accumulation of available statistical data. This article surveys the major approaches for the shortterm and the long-term morbidity forecasting. Their limitations and the practical application possibilities are pointed out. The paper presents the conventional time series analysis methods — regression and autoregressive models; machine learning-based approaches — Bayesian networks and artificial neural networks; case-based reasoning; filtration-based techniques. The most known mathematical models of infectious diseases are mentioned: classical equation-based models (deterministic and stochastic), modern simulation models (network and agent-based).