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APPLICATION OF BACKPACK ALGORITHMS TO PREVENT UNAUTHORIZED EXCHANGE OF INFORMATION BETWEEN DIFFERENT LEVELS USERS IN THE HIERARCHICAL SYSTEM OF PROTECTION AGAINST UNAUTHORIZED ACCESS
А.S. Zhuck80-912025-10-01Abstract ▼The problem of designing a secure system of protection against unauthorized access is considered. In particular, this article considers hierarchical data protection systems with cryptographic key distribution, namely, the problem of organizing access to file storages is considered. Although cryptographic key distribution can ensure the security of information from users who do not have access to it, the hierarchical access control system was not originally designed to solve the problem of protecting information from the dishonest actions of the user himself. Thus, the overall objective of the study is to prevent unauthorized exchange of information between users of different levels of a hierarchical system of protection against unauthorized access with cryptographic key distribution. To achieve the stated goal, the authors previously proposed to use the problems of Diophantine analysis, in particular the knapsack problem. Previously, the authors formulated the properties of the knapsack vector, applicable for improving the hierarchical system of protection against unauthorized access. In this article, the authors present the conditions for the injectivity of knapsack vectors. A comparative analysis of these conditions with the already established injectivity conditions is carried out. The analysis shows the need to formulate such conditions and the applicability of knapsack vectors that satisfy them for improving the hierarchical model of protection against unauthorized access. Based on the specified conditions, this article develops a recursive algorithm for constructing an injective multiplicative knapsack vector. The authors then analyze the possibility of its application for modeling a hierarchical mandatory model of information protection from unauthorized access. The analysis shows how already known algorithms for constructing knapsack vectors can be used as part of the developed algorithm. The authors also show where exactly in the developed system it is necessary to apply this algorithm to implement the properties required for hierarchical systems of protection against unauthorized access
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A MODEL OF A SUBSYSTEM FOR GENERATING CRYPTOGRAPHIC KEYS OF THE CYBERPHYSICAL SYSTEM INFORMATION PROTECTION SYSTEM
V. А. Golovskoy, А. V. Vinokurov2025-04-27Abstract ▼The study is devoted to improving the subsystem of information protection in the radio channels of a
cyberphysical system using the example of a robotic complex (RTC). Modern and promising critical conditions
for the use of RTCs are considered, which determine the sets of requirements for the characteristics
of both RTCs and their subsystems, such as the radio data transmission system (RS) and the information
security subsystem. One of the approaches to meeting the requirements is the unification of theseRTC subsystems, which can be divided conditionally into two scientific and technical tasks: unification of
radio protocols and unification of information security tools in RS radio channels. The paper presents the
practical problems obtained as a result of the analysis, which lie at the intersection of two areas of research
– RS and information security subsystems. A hypothesis has been formed about the potential for
effective resolution of one of these practical problems – providing an information protection system with
cryptographic keys - by including a cryptographic key generation subsystem (CKGS) from biometric data
used as the initial key information in the RTC information protection system. The proposed improvement
has several aspects – regulatory, economic, and technical. The paper examines only the scientific and
technical side of the issue, as a result of which a functional model of the CKGS is proposed, which provides
a study of the possibilities of the modeled subsystem for the implementation of the formulated principles
of functioning. The purpose of the work is to develop a model of the CKGS functioning for the cryptographic
information protection system in the RS RTC radio channels and the formation of its algorithmic
content. The object of research is a system of cryptographic information protection in RS radio channels.
The subject of the research is an algorithm for generating cryptographic keys for a cryptographic information
protection system in RS RTC radio channels. To achieve this goal, a class of abstractions involved
and a methodological apparatus are substantiated that uses the provisions of the theory of algorithms to
prove the existence of an algorithm that solves a formulated mass problem and has specified non-trivial
semantic properties. Research methods – analysis, analogy, synthesis, decomposition, abstraction. The
main mass problem and the hypothesis of its solvability are formulated. In order to test the hypothesis, the
corresponding theorem is formulated and proved. The proposed model makes it possible to prove the joint
effective feasibility of various information processing algorithms -
MULTIMODAL DATA FEATURE EXTRACTION METHOD FOR NETWORK ATTACK CLASSIFICATION
A.V. Balyberdin6-162025-07-24Abstract ▼An intrusion detection system (IDS) is an important component of corporate data network (CDN) protection. IDS analyzes network traffic and detects network attacks. Depending on the detection methods, IDS can be classified into the following types of systems: signature-based analysis systems, anomaly detection systems (ADS), and hybrid systems combining the aforementioned approaches. Recently, anomaly detection systems (IDS) have been actively developing. For anomaly detection systems, network attacks are anomalous behavior of network traffic consisting of a set of features or event attributes. Modern IDS are based on machine and deep learning methods, and therefore the detection of network attacks and anomalies is formulated as a classification and clustering problem. To solve these problems, methods for optimizing the feature space of network traffic are required. The aim of the work is to develop a feature extraction method based on a multimodal approach to representing network traffic data for classifying network attacks. The paper considers the analysis of relevant studies on feature extraction methods from various fields. The objective of the study is to improve classification efficiency using a multimodal representation of network traffic features. The result of the work is a method for extracting data features based on two modalities: a spectral representation of network traffic features and an image feature matrix. The novelty of the presented method lies in the application of the windowed Fourier transform method for network traffic events, followed by the calculation of spectral features for discrete signals, as well as the transformation of data features into an image matrix and its expansion to optimize the feature space using a convolutional neural network (CNN). Evaluation of the multimodal method showed that this method increased the classification accuracy for unbalanced classes of network attacks
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CONSTRUCTION OF AN OPTIMAL CONTROL TRAJECTORY IN AN INTELLIGENT SYSTEM IN THE ABSENCE OF OBSERVABLE VARIABLES
А.N. Tselykh , V. S. Vasilev , L.А. Tselykh , Е.S. Podoplelova224-2332025-07-24Abstract ▼Constructing optimal control in the complete absence of data on the system dynamics is a pressing problem. In this paper, we propose a solution to a finite-horizon linear quadratic problem (LCP) for a time-invariant system with a graph dynamics matrix. Unlike the control problem, stability and complete controllability of the system are not assumed. The construction of the control trajectory is controlled by the direction of increase in the change in the state of variables over a small number of steps, which is determined by the conditional principal eigenvector of the adjacency matrix of the graph model. The solution of classical optimal control is carried out in an autonomous mode and requires complete knowledge of the system dynamics. In the absence of complete knowledge of the system dynamics, solving optimal control problems for systems with uncertainty, including discrete linear systems, has attracted considerable interest in recent years. The main approach when complete information about the system is unavailable is the design of optimal control, in which the system parameters are initially determined, and then an algebraic equation in the dual space is solved. An important difference from the standard discrete control problem is that the control model was modified to estimate changes in the state of variables under controls transmitted through the dynamics matrix. The proposed algorithm using a graph matrix implements recurrent calculations of dynamic and adjoint equations, as well as the Powell method for solving a system of linear algebraic equations (SLAE). The authors introduced a new interpretation of the mathematical construction of the system dynamics matrix in a standard discrete control problem on a finite time interval, which can be used to design any controlled dynamic system with unobservable parameters.
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EVOLUTIONARY POPULATION METHOD FOR SOLVING THE TRANSPORT PROBLEM
B.К. Lebedev, О.B. Lebedev, Е.О. Lebedevа2022-11-01Abstract ▼The paper considers an evolutionary population method for solving a transport problem
based on the metaheuristics of crystallization of a placer of alternatives. We study a closed (or
balanced) model of the transport problem: the amount of cargo from suppliers is equal to the total
amount of needs at destinations. The goal of optimization is to minimize the cost (achieving a minimum
of transportation costs) or distances and the criterion of time (a minimum of time is spent on
transportation). The metaheuristics of the crystallization of a placer of alternatives is based on a
strategy based on remembering and repeating past successes. The strategy emphasizes «collective
memory», which refers to any kind of information that reflects the past history of development and
is stored independently of individuals. An ordered sequence Dk of routes is considered as a code
for solving the transport problem. The objects are routes, the alternatives are the set of positions P
in the list, where np is the number of positions in the list Dk. The set of objects Dk corresponds to
the set of all routes. The set of alternative states P of the object corresponds to the set of alternative
options for placing the object in the list Dk. The operation of the population evolutionary algorithm
for the crystallization of a placer of alternatives is based on a collective evolutionary
memory called a placer of alternatives. A scattering of solution alternatives is a data structure
used as a collective evolutionary memory that carries information about the solution, including
information about the realized alternatives of agents in this solution and about the usefulness of
the solution. A constructive algorithm for the formation of a reference plan by decoding the list Dk
has been developed. At each step t, the problem of choosing the next route in the sequence Dk and
determining the amount of cargo transported from the point of departure Ai to the point of destination
Bj along this route is solved. The developed algorithm is population-based, implementing the
strategy of random directed search. Each agent is a code for some solution of the transport problem.
At the first stage of each iteration l, a constructive algorithm based on the integral placer of
alternatives generates nk decision codes Dk. The formation of each decision code Dk is performed
sequentially in steps by sequentially selecting an object and position. For the constructed solution
code Dk, the solution estimate ξk and the utility estimate δk are calculated. An individual scattering
of alternatives Rk is formed and a transition to the construction of the next solution code is formed.
At the second stage of the iteration, the integral placer of alternatives formed at previous iterations
from l to (l-1) is summed with all individual placers of alternatives formed at iteration l.
At the third stage of iteration l, all integral utility estimates r*
αβ of the integral placer of alternatives
R*(l) are reduced by δ*. The algorithm for solving the transport problem was implemented in
C++ in the Windows environment. Comparison of the values of the criterion, on test examples,
with a known optimum showed that in 90% of the examples the solution obtained was optimal, in
2% of the examples the solutions were 5% worse, and in 8% of the examples the solutions differed
by less than 2%. The time complexity of the algorithm, obtained experimentally, lies within O(n2). -
OPTIMIZATION OF PROJECT SCHEDULING UNDER UNCERTAIN PARAMETERS
А. V. Bozhenyuk, О. V. Kosenko, М.V. Knyazeva2022-05-26Abstract ▼This article considers the problem of operational planning of one-subject production.
The organization of machine-building production is a complex set of works to determine the interrelated
indicators that characterize the activities of the enterprise. Enterprises of this type have a
complex hierarchical structure. It is also necessary to take into account that when planning the
production process, the number of parameters is large and not all of them can be accurately determined,
which affects the efficiency of the enterprise. To solve the problem of effective planning,
the optimality criteria for serial one-subject production were analyzed. One-subject production
includes those where parts of the same name are processed, that is, a production line is formed.
Consequently, the task of optimizing production is to distribute the entire set of work between the
machines and operators servicing this machine in such a way that the planned task is completed
within a given time and the total cost of completing the task is minimal. The article considers the
problem of assignment under uncertainty, carried out experimental calculations and analyzed the
results obtained, which justifies the use of the proposed apparatus of fuzzy sets for solving the
problem of production planning. It is concluded that under conditions of uncertainty, when there is
no exact or statistical information, the apparatus of fuzzy sets makes it possible to analyze theeffectiveness of production activities when setting parameters that reflect the possible values of the
system. In such cases, the use of fuzzy logic mechanisms in the problems of making production
decisions will make it possible to determine optimal or close to optimal solutions. -
HYBRID METHOD FOR SOLVING THE PROBLEM OF PLACEMENT OF DIGITAL COMPUTER DEVICES
L. A. Gladkov , N. V. Gladkova , M.J. Yasir2021-11-14Abstract ▼The problem of placing elements of digital computing technology is considered in the article.
The analysis of the current state of research on this topic is carried out, the relevance of the
problem under consideration is noted. The importance of developing new effective methods for
solving such problems are highlighted. The place of the placement problem in the general cycle ofthe design stage is shown. The importance of a high-quality solution to the placement problem
from the point of view of the successful implementation of subsequent design stages is noted. The
importance of minimizing connection delays in the design process of large-scale devices is noted.
A review and analysis of various models and criteria for evaluating the solution to the placement
problem is carried out. It was emphasized that the most important criterion is the length of the
joints, it has a significant impact on the technologies used in the design. A complex mathematical
formulation of the problem of placing elements of digital computing equipment has been completed.
Perspective approaches to solving design problems are analyzed, hybrid methods and models
for solving complex multicriteria optimization and design problems are described. The principles
of operation and the model of a fuzzy logic controller are described. The description of the used
fuzzy control scheme is given. The functions of various blocks of a fuzzy logic controller are determined.
The structure of a multilayer neural network that implements the Gaussian function is
proposed. The interaction of blocks of a fuzzy genetic algorithm is described. A model of a hybrid
algorithm for solving the placement problem is proposed. The control parameters of the fuzzy
logic controller are determined. The proposed hybrid algorithm is implemented as an application
program. A series of computational experiments to determine the effectiveness of the developed
algorithm and select the optimal values of the control parameters were carried out. -
A NEW ALGORITHM FOR CONSTRUCTING THE SHORTEST TOUR OF A FINITE SET OF DISJOINT CONTOURS ON A PLANE
А. А. Petunin, E.G. Polishchuk, S.S. Ukolov2021-04-04Abstract ▼The problem of tool path routing for the CNC thermal cutting machines is considered.
Pierce points are located at the parts bounding contours, consisting of straight-line segments and
circular arcs. Continuous cutting technique is used, each contour is cut out entirely, and no presampling
occurs, so cutting can start from any point on the contour. General problem of minimizing
the route length is reduced to minimizing the air move length. It is shown to be equivalent to
finding the shortest polyline with vertices on the contours. New algorithm for constructing such a
broken line for fixed order of contour traversing is proposed. The resulting solution is shown to be
a local minimum. Some sufficient conditions are described for the it to be also a global minimum,
which can be easily verified numerically, and some even visually. A technique is described for
automatically taking into account precedence constraints for the practically important case of
nested contours. This also decreases the size of the problem, which has a positive effect on the
optimization time. A heuristic routing algorithm based on the variable neighborhood search (VNS)
is proposed. Alternative approaches to the use of other discrete optimization methods along with
the proposed algorithm for constructing the shortest polyline for solving the complete problem of
continuous cutting, and the resulting difficulties of both theoretical and practical nature are described.
The generalization of the problem of continuous cutting to a wider class of problems of
(generalized) segment cutting is described, which makes it possible to advance in solving the problem
of intermittent cutting. The scheme of application of the proposed algorithm for solving problems
of generalized segment cutting is described. The results of numerical experiments are considered
in comparison with the exact solution of the GTSP problem. -
HYBRID METHOD FOR SOLVING THE MULTI-AGENT TRAVELING SALESMAN PROBLEM
V.А. Kostyukov, F.А. Houssein2025-04-27Abstract ▼In this research work, the problem of task allocation in a multi-agent system is considered, where
each agent is a robot, and each task is represented by a position, which should be visited by one agent.
This problem is very similar to the multi-agent traveling salesman problem, which, unlike the famous traveling
salesman problem, involves several traveling salesmen who visit a given number of cities exactly
once and return to the starting position with minimal travel costs. Therefore, the multi-agent traveling
salesman problem is analyzed as a representative of the task allocation problem. The multi-traveling
salesman problem is important for the field of route optimization and task allocation between several
agents. It includes two different, but interrelated subproblems: distribute cities among agents and determine
the order in which each agent visits cities. In the literature, there are 3 concepts for solving this
problem with respect to solving its two constituent subproblems: the optimization concept, where both
subproblems are solved simultaneously; The Cluster-First, Route-Second concept is where the question of
which tasks to assign to which salesman is first decided, and then the question of the order in which each
salesman solves his tasks is decided; The Route-First, Cluster-Second concept is where the question of the
order in which tasks should be visited is first decided, and then this cycle is divided between agents without
changing the order of visits in order to answer the question of which tasks each agent takes on. This
paper proposes a hybrid approach to solving the multiple traveling salesman problem (mTSP), which
combines the ideas of two well-known concepts: "First clustering, then routing" and "First routing, then
clustering" in order to obtain their positive aspects and get rid of their weaknesses. To evaluate the effectiveness
of the developed method, a comparative study was conducted using the classical method for solving
the multi-traveling salesman problem. The results were evaluated based on three key criteria: the
computational time to obtain a solution to the multi-travelling salesman problem, the total length of the
routes travelled by the salesmen, and the maximum route length among them. The analysis of the experimental
data showed that when using the proposed method, the maximum path length among the routes
travelled by the agents (load imbalance) is reduced by an average of 26%. -
THE MATHEMATICAL PROBLEM OF OPTIMAL CONTROL OF THE STRING
G. V. Kupovykh, A. G. Klovo , I. A. Lyapunova2020-11-22Abstract ▼It is generally accepted that optimal control problems or system design problems determine
for a given object or system of control objects a law or a certain control sequence of actions that
provide a maximum or minimum of a given set of system quality criteria. In this case, the speed
problem can be considered, i.e. the problem of bringing the system to a given state in the shortest
time. We also study the problems of minimizing a given functional for a fixed time of system management.
Optimal control is closely related to the choice of the most rational modes for managing
complex objects. A lot of works has been devoted to the problem of control, in addition, wellknown
mathematical schools are currently engaged in such research. In problems with concentrated
parameters, the systems under study are described by ordinary differential equations or
their systems. In this case, the Pontryagin maximum principle plays an important role in this
study. For partial differential equations, we talk about systems with distributed parameters. In thispaper, we investigate the possibility of synthesizing optimal control of a single system with distributed
parameters. A model of string oscillation under the influence of control functions under
boundary conditions is considered. The role of the choice of the functional to be minimized in creating
opportunities for the synthesis of optimal control. In this case, the control action is searched
for at each point of the time interval, which leads to the possibility of constructing it explicitly.
The conditions for the existence of optimal control everywhere in the corresponding functional
spaces are formulated. In a specific statement of the problem, everywhere optimal control is explicitly
constructed. -
MODIFIED GENETIC PROJECT PLANNING ALGORITHM IMPLEMENTED WITH THE USE OF CLOUD COMPUTING
А. А. Mogilev, V.M. Kureichik2020-07-20Abstract ▼The paper proposes a structure of a modified genetic algorithm for solving resource constrained
project scheduling problem implemented with the use of cloud computing, a computational
experiment was conducted, during which the results of the proposed algorithm were compared
with the best known, at the moment, results. Based on the results of the experiment, it was concluded
that the proposed algorithm can be used to plan the work of real projects, since it is possible
to draw up schedules for projects with the number of works n = 90 for an acceptable period of
time. When planning projects with the number of jobs n = 30, n = 60, n = 90, 120, the execution
time of the proposed algorithm was less than the execution time of the standard genetic algorithm
by 2.8, 4, 5.5 and 6.8 times, respectively. Due to the fact that the task of constructing a project
schedule taking into account limited resources is NP-difficult, the problem of creating new and
modifying existing methods for solving it remains relevant. For planning projects with a large
number of works, it is advisable to use cloud computing, since planning such projects can require
a lot of time and computing resources. In this regard, the algorithm proposed in this paper differs
from the existing ones by using cloud computing to distribute the load between workstations on
which this algorithm is simultaneously running. The use of modified operators in the genetic algorithm,
as well as the use of cloud infrastructure as a service for implementing a distributed genetic
algorithm, determines the scientific novelty of the study. -
GROUPING PREDICTORS IN COMBINED PIECEWISE LINEAR REGRESSION
S.I. Noskov , S.V. Belyaev120-1272025-10-01Abstract ▼The article provides a brief overview of publications on the application of combined structures containing known model forms as constituent elements in mathematical modeling of complex systems. In particular, the following are considered: an algorithm for estimating parameters for creating mathematical models of dynamic systems; structured mathematical models of an oxygen electrode and biological wastewater treatment; a combined model including ion exchange between calcium and copper; a combination of non-standard finite-difference schemes and the Richardson extrapolation method to obtain numerical solutions of two models of biological systems; a mathematical formulation of the problem and a heuristic approach to optimal planning of delivery routes in a multimodal system; a mathematical model for optimizing strategic and tactical decisions in all types of biomass-based supply chains; a method for developing models of various types for elements of chemical-engineering systems taking into account various types of available information and combining these models into a single complex. Two variants of the problem statement for calculating the estimates of the parameters of a combined piecewise linear regression are formulated: with a non-empty and empty intersection of the index sets that define the composition of the independent variables in the linear and piecewise linear components of the model. It is shown that in both cases, when the sum of absolute deviations of approximation errors is selected as the loss function, both variants are reduced to linear-Boolean programming problems. Two versions of a combined piecewise linear regression model of revenue of the mining and metallurgical company Severstal are constructed. The following production volumes are used as independent variables of the model: hot-rolled, cold-rolled and galvanized sheet, sheet with another metal coating, sheet with a polymer coating, rolled products, hardware products.
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DEVELOPMENT OF A METHOD FOR SOLVING THE PROBLEM OF TASK ALLOCATION IN A MULTI-AGENT SYSTEM
V.А. Kostyukov , F.А. Houssein144-1552025-10-01Abstract ▼This paper considers the problem of task distribution within a multi-agent system, where each agent is an autonomous robot, and each task corresponds to a point in a two-dimensional environment that one of the agents must visit. This problem is essentially similar to a multi-agent version of the classical traveling salesman problem, where several agents are involved instead of one participant. Each of them must go through a unique route covering a certain set of points. In this regard, a study of the multi-agent traveling salesman problem is conducted as one of the formats for setting the problem of distributing goals among agents. This problem is of great importance in the field of routing and optimal task distribution. Its solution includes two closely related subproblems: determining the set of points assigned to each agent and constructing the optimal route for visiting them. There are three main approaches to solving this problem in the scientific literature: Optimization approach, where both subproblems are solved jointly; Cluster-First, Route-Second model, where tasks are first distributed among agents, and then routes are built;
The Route-First, Cluster-Second model assumes initial optimization of the route for all points with its subsequent division between agents without changing the order of visits. In this paper, a hybrid method is proposed that combines elements of the Cluster-First, Route-Second and Route-First, Cluster-Second approaches. The goal is to combine the strengths of both concepts and minimize their drawbacks. To test the effectiveness of the developed method, a comparative study was conducted. The evaluation was carried out according to three main metrics: the time spent on constructing a solution, the total length of all routes, and the maximum route length among all agents. The experimental results showed that the use of the proposed method allows for a reduction in the maximum route length (thereby reducing the load imbalance between agents) by an average of 26%. -
A METHOD FOR PLANNING ROBOTIC MOVEMENTS IN COMPLEX CONFLICT ENVIRONMENTS WITH POLYGONAL OBSTACLES
V.А. Kostyukov2026-04-29Abstract ▼When developing algorithms for real-time robot path planning, the problem of performance limitations of the corresponding classical algorithms arises. This paper considers a method for planning robot movements in a two-dimensional complex conflict environment. For planning in complex environments, a hybrid planning algorithm is proposed, based on a combination and synthesis of the classical cellular decomposition algorithm and a recently proposed algorithm based on the characteristic visibility graph. This algorithm involves a preliminary analysis of the complexity of the obstacle scene, based on the results of which one of the two specified particular algorithms is selected. It is shown that this approach can significantly overcome the limitations of both of these algorithms. A disturbance avoidance method based on the apparatus of characteristic probability functions is described in a compact form, and its relationship with planning methods in complex environments is demonstrated when solving corresponding problems of global optimization of the probability of successful completion of a target trajectory. The developed approach examines the relationship between the probability of successful path completion in a source field and the corresponding risk function. To solve global robot motion planning problems in complex conflict environments, the proposed hybrid algorithm is first proposed for constructing a family of initial curves within the appropriate feasible motion corridors, ignoring sources. A family of local optimization problems is then solved within the feasible motion corridors, taking sources into account. Next, the trajectory with the maximum probability of successful completion or the normalized safe motion function is selected
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APPLICATION OF THE MIXED PARAMETER ESTIMATION METHOD IN THE CONSTRUCTION OF A HOMOGENEOUS NESTED PIECEWISE LINEAR REGRESSION OF THE FIRST TYPE
S.I. Noskov , А. P. Medvedev , I. D. Kirillov102-1092026-09-10Abstract ▼The paper is devoted to the development of an algorithm for identifying the parameters of a homogeneous nested piecewise linear regression of the first type – a model that is in demand when analyzing complex systems whose behavior cannot be adequately described by smooth functions. The review part of the work systematizes modern publications illustrating the use of piecewise linear forms in various subject areas: from modeling energy consumption and nonlinear control systems to image processing, reconstruction of genetic networks, and filtering of geophysical data. The novelty of the study lies in the fact that for the first time for this class of models an identification algorithm based on the mixed estimation method (MEM) is proposed, which allows flexible combination of two different quality criteria. It is shown that by introducing additional Boolean variables and auxiliary constraints, the original optimization problem is reduced to a standard linear Boolean programming problem, which makes it possible to use available numerical methods for its solution. The effectiveness of the developed algorithm is demonstrated on real data of the mining and metallurgical company Norilsk Nickel for 2010–2024. The dependent variable is revenue, and the predictors are the production volumes of nickel, palladium, copper and platinum. Two alternative models are constructed – using the classical least absolute deviations method and the proposed mixed estimation method. A comparative analysis shows that the second model has a slightly higher average percentage error, but significantly outperforms in the magnitude of the maximum error on the control subsample, which makes it preferable in conditions where outliers are critical. The results obtained confirm the practical value of MEM for constructing interpretable and robust regression dependencies
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MODERN APPROACHES TO SOLVING THE 3D BIN PACKING PROBLEM
М.М. Sorokin , L. А. Gladkov , N. V. Gladkova131-1502026-09-10Abstract ▼The article is devoted to the consideration of current trends and approaches to solving the urgent optimization problem of three-dimensional bin packing problem. The importance of building effective methods for solving this problem is due to the rapid growth of e-commerce, where achieving even incremental improvements in container filling density can lead to significant reductions in freight transportation and storage costs. The article provides an analysis of various types of problems and suggests a classification of bin packing problems according to various criteria, including: offline and online packing, by dimension, by type and quantity of containers and cargo. The formulation of the classical optimization knapsack problem is given and various options for constraints due to the specifics of the tasks being solved are considered. A brief overview of the main approaches to solving the problem is given. The analysis and generalization of the characteristic features of the application of metaheuristic approaches based on the use of evolutionary and bioinspired algorithms and machine learning methods is carried out, their advantages and disadvantages are noted. Due to the complexity of the problem under consideration, it is proposed to actively use known and develop new modifications of metaheuristic algorithms that make it possible to find quasi-optimal solutions in polynomial time. The analysis of known machine learning methods and bioinspired algorithms is given, the principles of their operation are described, their main features, advantages and disadvantages are highlighted, and the prospects for their development and application to solve NP-complete combinatorial optimization problems are noted. A generalized principle of operation of metaheuristic algorithms is given. A comparative analysis of the application of various optimization methods has shown the effectiveness of using metaheuristic methods to solve the problem of three-dimensional packaging.
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AN ONTOLOGICAL APPROACH TO DISTRIBUTED COMPUTING TECHNOLOGIES IMPLEMENTATION ON THE INTERNET
V. M. Kureichik , I.B. Safronenkova2020-11-22Abstract ▼Distributed computing technologies development has allowed uniting geographically distributed
resources and has provided an opportunity for effective resource intensive problemsolving
in various fields of science and technology. At the same time a set of problems, which demands
the development of new approaches, taking into account contemporary Internet technologies
implementation, has risen. In this paper a problem of workload relocation in distributed computer-
aided design system (DCAD) operating in the “fog” environment was considered. The goal
of this paper is ontological approach development to workload relocation problem-solving in
DCAD taking into account some “fog” environment features. The ontological approach involves
an ontological procedure implementation, which allows “filtering” the candidate-nodes, which
have insufficient resources for workload relocation. The scientific novelty of this paper is ontological
models using for workload relocation problem-solving in DCAD. It allows reducing the number
of candidate-nodes in the “fog” for workload relocation, thereby contributing to reduce the
time of location process modeling and, consequently, the total time of workload relocation problem-
solving is also reduced. The fundamental difference of presented approach is domain
knowledge, represented in ontological model, applying for workload relocation problem-solving.
The experimental study results have shown the expediency of ontological analysis for workload
relocation problem-solving .
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