Article

Article title HYBRID MODEL OF SOLVING OPTIMIZATION DESIGN PROBLEMS
Authors L. A. Gladkov, N. V. Gladkova, S. N. Leiba
Section SECTION I. DESIGN AUTOMATION
Month, Year 04, 2018 @en
Index UDC 519.712.2
DOI
Abstract The methods of optimization tasks of computer-aided design in circuits of digital electronic computing equipment are considered herein. The relevance and importance of developing new effective methods for solving similar problems are noted. The formulation of the problem of placing elements in circuits of electronic equipment is given, restrictions of the domain of admissible solutions are chosen. A technique for determining the quality of the solution obtained is proposed on the basis of a complex normalized assessment of the amounts of fines for several selected criteria. A new hybrid model of the problem is proposed on the basis of a combination of evolutionary search methods, a mathematical apparatus of fuzzy logic and the possibilities of parallel organization of the computational process. New modifications of the main genetic operators have been developed. A modified migration operator is proposed to exchange information between solution populations in the process of performing parallel computations. The structure of the parallel hybrid algorithm is developed. To exchange solutions between populations, it was proposed to use the island and buffer models of the parallel genetic algorithm. The implementation of the fuzzy control module based on the use of a multilayer neural network and the Gaussian function is proposed. To improve the quality of the results obtained, a fuzzy logic controller that regulates the values of the parameters of the evolution process is included in the evolution of expert information. The basic principles of the fuzzy control unit are formulated. The structural scheme of the developed hybrid algorithm is presented. Features of software implementation of the proposed hybrid algorithm are considered in detail. The structure of the interface is described, the main elements of the graphic interface of the developed application are presented. A brief description of the computational experiments that confirm the effectiveness of the proposed method is presented.

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Keywords Design automation; genetic algorithm; evolutionary computation; fuzzy control; parallel computing; fuzzy logic controller.
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