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• HYBRID APPROACH THE JOINT SOLUTION OF PLACEMENT AND TRACING PROBLEMS

  L.A. Gladkov , N. V. Gladkova , Dzhabbar Yasir Yasir Mukhanad

  2020-11-22

  Abstract ▼

  The article proposes an integrated approach to solving the problems of placing and tracing elements
  of circuits of electronic computing equipment. The approach is based on the joint solution of
  placement and tracing problems using fuzzy genetic methods. A description of the problem under
  consideration is given and a brief analysis of existing approaches to its solution is performed. The
  article discusses integrated approaches to solving optimization problems of computer-aided design of
  digital electronic computing equipment circuits. The urgency and importance of developing new
  effective methods for solving such problems is emphasized. It is noted that an important direction in
  the development of optimization methods is the development of hybrid methods and approaches that
  combine the advantages of various methods of computational intelligence. The article describes the
  following main points: the structure of the proposed algorithm and its main stages; modified genetic
  crossover operators; models for the formation of the current population are proposed; modified heuristics,
  operators and strategies for finding optimal solutions. The results of computational experiments
  are presented. The experiments carried out confirm the effectiveness of the proposed approach.
  In conclusion, a brief analysis of the results obtained is given.

• 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.