Search

Search Results

• MULTILEVEL APPROACH FOR HIGH DIMENSIONAL 3D PACKING PROBLEM

  V. V. Kureichik, А. Е. Glushchenko

  2020-07-20

  Abstract ▼

  The article considers one of the important combinatorial optimization problems, the problem
  of 3D packing of different elements in a fixed volume. It belongs to the class of NP-complex and difficult
  optimization problems. The paper presents and describes the formulation of the 3D packing
  problem, introduces a combined objective function that takes into account all the restrictions. Due to
  the complexity of this task, a multilevel approach is proposed. It is consisting in dividing the 3D packing
  problem into 3 subtasks and solving each subtask in a strict order. Moreover, for each of the
  subtasks a unique set of objects is defined that are not repeated in the remaining subtasks. To implement
  a multi-level approach, the authors developed a combined bio-inspired algorithm based onevolutionary and genetic search. This approach can significantly reduce the time to obtain the result,
  partially solve the problem of preliminary convergence of the algorithms and obtain sets of quasioptimal
  solutions in polynomial time. A software package was developed and computer-based algorithms
  for automated 3D packaging based on a combined bio-inspired search were implemented.
  A computational experiment was conducted on test examples (benchmarks). The packaging quality
  obtained on the basis of the developed combined bio-inspired algorithm is on average 5 % higher
  than the packaging results obtained using known algorithms, and the solution time is less than 5 % to
  20 %, which indicates the effectiveness of the proposed approach. The series of tests and experiments
  carried out made it possible to refine the theoretical estimates of the time complexity of the packaging
  algorithms. In the best case the time complexity of the O (n2) algorithms; in the worst, O (n3).

• SOLUTIONS’ ENCODING IN EVOLUTIONARY METHODS FOR INSTRUMENTAL DESIGN PLATFORM

  E.V. Kuliev, А. А. Lezhebokov, М. М. Semenova, V.A. Semenov

  2020-07-20

  Abstract ▼

  The article considers current issues and analyzes the problems of three-dimensional integration
  and three-dimensional modeling that arise at the design stage during the solution of the
  problem of optimal planning of components of large and extra-large integrated circuits and case
  devices of electronic computing equipment. The main advantages of applying the principles of
  three-dimensional integration are presented and described in sufficient detail, which allow efficiently
  organizing the production of personalized electronics, optimally planning the configuration
  of large and ultra-large integrated circuits, taking into account thermal and energy characteristics.
  In the course of research, the authors developed an approach to encoding decisions based on
  an intelligent mechanism, which is characterized by the presence of built-in means of control of
  acceptable decisions. One of such tools that have experimentally proven their effectiveness is the
  built-in mechanism of “deadly mutations”, which takes into account the status of genes and predetermined
  restrictions on the final configuration of the housing of the designed device. A series of
  general approaches and specific algorithms for solving the planning problem based on the results
  of research by the author's team and modern approaches to solving NP-complete problems are
  proposed. The most important practically significant result of the research of the indicated problem
  is the developed software and instrumental design platform in the modern cross-platform Java
  programming language. The selected development technology allows you to use all the main advantages
  of modern multi-core and multi-processor architectures, to use software multi-threading
  to implement parallel schemes for solving combinatorial problems. The software and tool platform
  has a user-friendly interface, which allows you to effectively manage the process of solving the
  problem of planning the components of large and ultra-large integrated circuits of threedimensional
  integration by visualizing key performance indicators of algorithms on graphs and in
  text statistics blocks. The developed application software made it possible to carry out a series of
  computational experiments based on random data sets, as well as on open-data boron benchmarks
  for such tasks. The results of experimental studies have confirmed the theoretical estimates of the
  time complexity and effectiveness of the proposed approaches and algorithms, including the genetic
  algorithm, which uses the new decision coding mechanism proposed in the work.

• DEVELOPMENT OF BIOHEURISTICS FOR CREATING AN INTELLECTUAL SUBSYSTEM FOR MAKING EFFECTIVE DECISIONS OF NP-HARD AND NP-DIFFICULT COMBINATORY-LOGICAL PROBLEMS ON GRAPHS

  D. V. Zaruba , E. V. Kuliev , D.Y. Zaporozhets , M. M. Semenova

  2021-11-14

  Abstract ▼

  The article is devoted to the solution of new topical problems that have arisen in the conditions
  of the modern development of information and nanometer technologies in the field of design,
  as well as the development of new innovative methods that provide effective solutions in polynomial
  time. The article deals with the problem of solving NP-hard problems. The description of the
  procedure for measuring the complexity of the problem is presented the features of NP-hard and
  NP-difficult combinatorial logic problems are described. The main differences between the tasks
  are presented, as well as the problems that one has to face when solving this type of task. The general
  decision-making scheme is presented, consisting of the problem formulation; decisionmaking;
  signal in automatic systems and feedback. At the second stage (formation and selection of
  solutions), the solution is based on a bioinspired algorithm for finding solutions to the traveling
  salesman problem. To solve this problem, a modified bioinspired algorithm based on the behaviorof an ant colony was developed. Unlike other optimization methods, metaheuristic algorithms can
  find global optimal solutions for problems where there are many local solutions due to their random
  nature. These reasons have led to the widespread use of such algorithms in solving various
  optimization problems. Bioinspired algorithms are becoming a new revolution in the field of solving
  optimization problems. The statement of the traveling salesman problem is presented, as well
  as the solution of the problem on the basis of the ant algorithm. Algorithms such as genetic algorithms
  and PSO can be very useful, but they still have some disadvantages in solving multimodal
  optimization problems. These algorithms can find optimal solutions regardless of the physical
  nature of the problem. In the framework of experimental studies, the analysis of the work of
  bioinspired algorithms was carried out: the algorithm of a flock of bats, the bacterial algorithm
  and the ant algorithm.

• INTELLIGENT SUBSYSTEM FOR DECISION SUPPORT BASED ON BIOLOGICALLY PLAUSIBLE ALGORITHMS FOR SELF-ORGANIZATION

  E.V. Kuliev , M.P. Krivenko, М.М. Semenova, S. V. Ignatieva

  2021-11-14

  Abstract ▼

  The article discusses the basic concepts and definitions of decision support systems based
  on self-organization. Decision Support Systems refers to a range of interactive computer systems
  that help to use data, models, and knowledge to solve semi-structured, unstructured, or unstructured
  problems. The diagram of the basic structure of the decision support system is shown and
  described. Three main components of Decision Support Systems are considered, and a case is
  described when the fourth component of a decision support system - a knowledge-based management
  system - can be applied. The article offers a description of an intelligent decision support
  system. Examples of specialized intelligent decision support systems include intelligent marketing
  decision support systems and medical diagnostics systems, flexible manufacturing systems. The
  problems associated with making optimal decisions occupy an important place in computer-aided
  design and require improving methods and means of supporting optimal design processes at various
  stages. Self-organization algorithms inspired by wildlife are considered. Bioinspired algorithms
  are a representative class of self-organization algorithms. Bio-inspired computing mimics
  nature and uses the underlying concepts and behavior of these systems to solve complex problems.
  The article describes the algorithm for bats. An experimental analysis of the process of applying
  the self-organization algorithm in decision-making systems is carried out.