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• 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.