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• CLASSIFICATION AND ANALYSIS OF EVOLUTIONARY METHODS OF EVA BLOCK LAYOUT

  Y.V. Danilchenko, V.I. Danilchenko, V. M. Kureichik

  2020-07-20

  Abstract ▼

  Currently, there is a large increase in the need for the design and development of radioelectronic
  devices. This is due to increasing requirements for radio-electronic systems, as well as
  the emergence of new generations of semiconductor devices. In this regard, there is a need to develop
  new tools for automated layout of EVA blocks. There are a number of problems that complicate
  the actual representation of knowledge in CAD and are probably solvable at the current level
  of cognitive science development. The problem of stereotyping and the problem of coarsening are
  interrelated and need to create hybrid models of representation. The paper deals with the problem
  of solving the problem of EVA block layout in the design of radio-electronic equipment. The purpose
  of this work is to find ways to optimize the planning of EVA block layout using a genetic
  algorithm. The relevance of the work is that the genetic algorithm can improve the quality of layout
  planning. These algorithms allow you to improve the quality and speed of layout planning. The
  scientific novelty lies in the search and analysis of effective methods for composing EVA blocks
  using genetic algorithms. The main difference from the known comparisons is in the analysis of
  new promising algorithms for composing EVA blocks. Result of work. The paper shows the disadvantages
  of traditional algorithms for searching for a suboptimal EVA plan. Descriptions of modern
  models of evolutionary and other calculations are given. Genetic algorithms have a number of
  important advantages – adaptability to a changing environment, the evolutionary approach makes
  it possible to analyze, Supplement and change the knowledge base depending on changing conditions,
  as well as quickly create optimal solutions. If you apply genetic algorithms and preprocessing
  heuristics to provide optimal initial solutions, you can achieve more productive use of
  algorithms. Known genetic algorithms converge quickly, but they lose population diversity, which
  affects the quality of the solution. To balance data, the solution is corrected using efficient operators
  or stable mutation.

• AUTOMATED STRUCTURAL-PARAMETRIC SYNTHESIS OF A STEPSED DIRECTIONAL RESPONDER ON CONNECTED LINES BASED ON A GENETIC ALGORITHM

  Y. V. Danilchenko , V.I. Danilchenko, V. M. Kureichik

  2020-11-22

  Abstract ▼

  An automated approach to the structural-parametric synthesis of a stepped directional coupler
  on connected lines based on a genetic algorithm (GA) is described, which makes it possible to
  create an algorithmic environment in the field of genetic search for solving NP complete problems,
  in particular, the structural-parametric synthesis of a stepped directional coupler on connected
  lines. The purpose of this work is to find ways of structural-parametric synthesis of a stepped directional
  coupler on coupled lines based on the bionspiration theory. The scientific novelty lies in
  the development of a modified genetic algorithm for automated structural-parametric synthesis ofa stepped directional coupler on connected lines. The problem statement in this work is as follows:
  to optimize the synthesis of passive and active microwave circuits by using a modified GA. A fundamental
  difference from the known approaches in the use of new modified genetic structures in
  automated structural-parametric synthesis, in addition, a new method for calculating a stepped
  directional coupler on connected lines based on a modified GA is righteous in the work. Thus, the
  problem of creating methods, algorithms and software for automated structural synthesis of microwave
  modules is currently of particular relevance. Its solution will improve the quality characteristics
  of the designed devices, reduce design time and costs, and reduce the requirements for
  developer qualifications.

• METAHEURISTICS BASED ON THE BEHAVIOR OF A COLONY OF WHITE MOLES

  Y.V. Danilchenko, V. I. Danilchenko, V. М. Kureichik

  132-140

  2021-08-12

  Abstract ▼

  Optimization algorithms inspired by the natural world have turned into powerful tools for solv-ing complex problems. However, they still have some disadvantages that require the study of new and more advanced optimization algorithms. In this regard, when solving NP complete problems, there is a need to develop new methods for solving this class of problems. One of these methods can be metaheuristics based on the behavior of a colony of white moles. This paper proposes a new metaheuristic algorithm called the blind white moles algorithm. This algorithm was developed based on the social behavior of blind moles in search of food and protecting the colony from intruders. The proposed solution will be able to overcome many disadvantages of conventional optimization algo-rithms, including falling into the trap of local minima or a low convergence rate. The purpose of this work is to develop an algorithm for optimizing a complex objective function. The scientific novelty lies in the development of a genetic algorithm based on the behavior of a colony of white moles for solving NP complete problems. The problem statement in this paper is as follows: to optimize the search for solutions to complex functions by applying an algorithm based on the behavior of a colony of white moles. The practical value of the work lies in the creation of a new search architecture that allows using the developed algorithm for the effective solution of NP complete problems, as well as conducting a comparative analysis with existing analogues. The fundamental difference from the known approaches is in the application of a new bioinspired search structure based on the behavior of a colony of white moles, which will allow to exclude falling into a local minimum or a low conver-gence rate. The presented results of the computational experiment showed the advantages of the pro-posed multidimensional approach to solving the problems of placing VLSI elements in comparison with existing analogues. Thus, the problem of creating methods, algorithms and software for solving NP complete problems is currently of particular relevance

• AUTOMATED STRUCTURAL-PARAMETRIC SYNTHESIS OF A STEPSED DIRECTIONAL RESPONDER ON CONNECTED LINES BASED ON A GENETIC ALGORITHM

  Y. V. Danilchenko , V.I. Danilchenko, V. M. Kureichik

  2021-07-18

  Abstract ▼

  All major manufacturers go to a decrease in the dimensions of modern microelectronic devices.
  This leads to the transition to new standards for designing and manufacturing SBSS.
  The well-known automated design algorithms are not fully able to implement new requirements
  when designing a SBI. In this regard, when solving the tasks of design design, there is a need todevelop new methods for solving this class task. One of these techniques can be a hybrid multidimensional
  search system based on a genetic algorithm (GA). An automated approach to the design
  of the SB based on a genetic algorithm is described, which makes it possible to create an algorithmic
  medium in the field of multidimensional genetic search to solve the NP full tasks, in particular
  the placement of the VSA elements. The purpose of this work is to find ways to place the elements
  of the SBI based on the genetic algorithm. The scientific novelty is to develop a modified
  multidimensional genetic algorithm for automated design of super-high integrated circuits. The
  formulation of the problem in this paper is as follows: optimize the placement of the ELEMENTS
  of the SBI by using, multidimensional modified hectares. The practical value of the work is to create
  a subsystem that allows you to use the developed multidimensional architecture, methods and
  algorithms to effectively solve the tasks of the design design of the SDI, as well as conduct a comparative
  analysis with existing analogues. The fundamental difference from the well-known approaches
  in the application of new multidimensional genetic structures in the automated design of
  the SBI, in addition, the modified genetic algorithm was righteous. The results of the computational
  experiment showed the advantages of a multidimensional approach to solving the tasks of placing
  the Elements of the SBI compared to existing analogues. Thus, the problem of creating methods,
  algorithms and software for the automated placement of the SBS elements is currently of particular
  relevance. Its solution will improve the qualitative characteristics of the designable devices,
  will reduce the timing and costs of design.

• METAHEURISTIC OPTIMIZATION METHOD BASED ON THE STEM CELL BEHAVIOR MODEL

  Y. V. Danilchenko , V.I. Danilchenko, V.M. Kureichik

  2022-05-26

  Abstract ▼

  The paper discusses optimization methods that are based on processes occurring in nature. Such
  methods have become increasingly used to solve complex problems. However, such methods have some
  drawbacks, which stimulates the development of new and more advanced optimization methods. Solving
  NP complete problems requires optimal methods that will meet all design requirements, so there is a
  need to develop new and more advanced methods for solving this class of problems. As such a method,
  the authors propose an optimization method based on a model of the behavior of stem cells in the natural
  environment. The conducted studies of the proposed method provide solutions that can overcome
  many of the shortcomings of standard optimization approaches, such as getting into the local optimum
  or low convergence rate of the algorithm based on the method under consideration. The purpose of this
  work is to develop an optimization method and an algorithm based on it for solving a complex objective
  function. The scientific novelty lies in the development of an optimization method based on the stem cell
  behavior model for solving NP complete problems. The aim of the work is to create conditions for theoptimal search for a solution to complex functions by applying the search method and, based on it, an
  algorithm for the behavior of stem cells. The practical value of the work lies in the development of a new
  metaheuristic optimization method for the efficient solution of NP complete problems. Also in the work,
  a comparative analysis with well-known competitors was carried out. The main difference of the proposed
  method from other known methods is the use of a new approach of bioinspired search based on
  the behavior of stem cells, which, as shown by practical comparison, has an advantage over known
  analogues. The results of a practical comparison of methods and algorithms based on them showed the
  advantages of the approach proposed in the work on known test functions. After analyzing the problem
  of creating methods, algorithms and software for solving NP complete problems, we can conclude that
  the development of such approaches is currently an urgent task.

• DEFINITION OF FUZZY CONDITIONS AND ANALYSIS OF EXISTING SOLUTIONS TO THE PROBLEM OF EVACUATION IN EMERGENCY SITUATIONS

  Y. V. Danilchenko, V.I. Danilchenko, V.М. Kureichik

  2023-02-27

  Abstract ▼

  Quantification in collective behavior and decision-making in fuzzy conditions is crucial to
  ensure the health and safety of the population. The task of modeling and predicting behavior in
  fuzzy conditions, as is known, has increased complexity due to a large number of factors from
  which an NP-complete multi-criteria problem is formed. There is a difficulty in quantifying the impact of fuzzy factors using a mathematical model. In this regard, the paper proposes a stochastic
  model of human decision-making to describe the empirical behavior of subjects in an experiment
  simulating an emergency scenario. The developed fuzzy model combines fuzzy logic into a
  conventional model of social behavior. Unlike existing models and applications, this approach
  uses fuzzy sets and membership functions to describe the evacuation process in an emergency
  situation. The purpose of this work is to define fuzzy rules and analyze existing solutions. The scientific
  novelty lies in the formation of a set of factors that form fuzzy rules for making dynamic
  decisions. The problem statement in this paper is as follows: to form a set of factors affecting the
  behavior of pedestrians, which are modeled as fuzzy input data. The practical value of the work
  lies in the creation of a new set of fuzzy rules that allows them to be used in the evacuation algorithm
  for the effective solution of the task. The fundamental difference from the known approaches
  is in the application of a new set of fuzzy rules, which contains factors: perception, intention, attitude.
  To implement the proposed model, the process of social behavior during evacuation, independent
  variables are determined. These variables include measurements related to social factors,
  in other words, the behavior of individual subjects and individual small groups, which are fundamental
  at an early stage of evacuation.

• A BIOINSPIRED APPROACH TO SOLVING THE PROBLEM OF 3D PACKAGING

  V.I. Danilchenko , V.V. Bova , М. М. Semenova , S.V. Ignateva , М. B. Shayliev

  2026-02-27

  Abstract ▼

  This article examines one of the most important combinatorial optimization problems – three-dimensional packaging. Optimizing three-dimensional packaging reduces costs and improves logistics efficiency, making it relevant for industry. This paper analyzes classical approaches such as greedy algorithms and dynamic programming, as well as widely used methods, including evolutionary algorithms and local search. An analysis of existing methods, including greedy search, dynamic programming, evolutionary algorithms, and local search, revealed their key characteristics and identified suitable areas of application. In the context of this analysis, an overview of the key methods that dominated during certain historical periods is presented. The analysis includes consideration of the application conditions of various methods, their effectiveness for specific types of problems, as well as their advantages and limitations.
  A multi-level search algorithm is presented that combines the advantages of traditional and modern optimization methods. This multi-level algorithm improves the accuracy of the packaging problem solution through dynamic parameter adjustment. A software package for solving the three-dimensional packaging optimization problem using bioinspired algorithms has been developed. A computational experiment was conducted on test examples (benchmarks). The packing quality obtained using the developed combined bioinspired algorithm is, on average, 7% higher than the packing results obtained using known algorithms, while the solution time is 7% to 25% shorter, demonstrating the effectiveness of the proposed approach. A series of tests and experiments allowed us to refine theoretical estimates of the time complexity of packing algorithms. In the best case, the time complexity of the algorithms is O(n²), and in the worst case, O(n³).

• INTELLIGENT METHODS OF PARAMETRIC FORECASTING AND OPTIMIZATION OF UAV TRAJECTORIES

  V.I. Danilchenko , V.V. Bova

  263-276

  2025-12-30

  Abstract ▼

  This paper examines the problem of intelligent parametric forecasting and trajectory optimization for unmanned aircraft systems (UAS) using evolutionary algorithms and machine learning methods. The relevance of the study stems from the multi-criteria and high complexity of UAS trajectory generation processes, as well as the need for accurate and timely assessment of its flight parameters. This is particularly important for ensuring the reliability, safety, and efficient performance of flight missions in UAS operating conditions, including scenarios related to the operation of critical infrastructure facilities. The objective of the study is to improve the accuracy of trajectory parameter diagnostics and the reliability of parametric forecasting of UAS trajectories under conditions of uncertainty and the multi-criteria nature of the problem. The paper proposes a hybrid approach incorporating a genetic algorithm (GA), a particle swarm algorithm (PSO), and an XGBoost machine learning model that provides adaptive assessment of the quality of the generated solutions. A computational software package has been implemented, including selection, recombination, mutation, and elite inheritance mechanisms, as well as a machine learning module for validating route trajectories and associated parameters. A computational experiment was conducted, which compared the effectiveness of GA and PSO under various operating scenarios. Testing was performed on industry-specific datasets with varying numbers of iterations. The computational experiment revealed the advantage of the genetic algorithm, namely, a 14–17% improvement in the quality of design solutions. The results of the study demonstrate high adaptability and practical applicability in modeling, parametric forecasting, and routing tasks, and also indicate the potential for integration with intelligent UAS navigation and monitoring systems. The article's materials are of practical interest to specialists in the field of UAS development and operation, as well as to researchers working on multi-criteria route planning, parametric forecasting, and improving the reliability of UAS operations.

• THE USE OF DISTRIBUTIVE SEMANTICS IN THE IDENTIFICATION OF SIGNIFICANT COMBINATIONS OF TITLES OF SEVERAL TEXT COLLECTIONS IN THE FORMALIZATION OF LINGUISTIC EXPERT INFORMATION

  V.I. Danilchenko, V.M. Kureichik

  2022-08-09

  Abstract ▼

  The paper discusses methods of forming special models for the representation of various sets
  of knowledge in various information systems. The work is devoted to the application of distributive
  semantics in the identification of significant combinations in one subject area (PRO) within the
  framework of the formalization of linguistic expert information (LEI). The paper applies an approach
  to the formalization of LEI based on a set of analytical methods, where linear algebra is used as
  models. This approach makes it possible to initialize the procedure for the automatic formation of
  hierarchical architectures of LEI or dendrograms when identifying significant combinations of titles
  of several collections of texts. The scientific novelty lies in the proposed analytical approach using
  distributive semantics in identifying significant combinations of titles of several collections of texts,
  which allows for the analysis and processing of linguistic expert information. A distinctive characteristic
  of the proposed approach is the ability to formalize the ABM "Global Optimization Methods"
  based on the synthesis of various already existing hierarchies of the ABM under consideration. The
  paper aims to create conditions for the formalization of the LEI by applying distributive semantics
  when identifying significant combinations of titles of several collections. The practical value of the
  work lies in the development of a new approach to the formalization of LEI, taking into account distributive
  semantics when identifying significant combinations of titles of several collections of texts.
  The ontology in owl format "Methods of global optimization" in the program "Protege" is also built
  in the work. The ontology is built on the basis of related data about. The ontology constructed in this
  work complements the search structure within the framework of the considered PRO and can be
  supplemented and developed in the future.