Article

Article title PLACEMENT CIRCUIT ELEMENTS OF ELECTRONIC COMPUTING DEVICES BASED ON HYBRID INTELLIGENT METHODS
Authors L.A. Gladkov, N.V. Gladkova, S.N. Leiba
Section SECTION I. MODELING AND DESIGN
Month, Year 04, 2015 @en
Index UDC 658.512.2.011.5
DOI
Abstract In this paper we consider the problem of placement of circuit elements of electronic computing equipment on the switching field. This problem relates to the problems of the design phase of the design of electronic computing equipment and is NP-complete. Problem is set to deploy elements of circuits of electronic computing equipment on the set of predetermined positions of the discrete operating field. An approach to the solution of the problem through the use of a modified genetic algorithm. The technique of encoding solutions to perform genetic search. A detailed example illustrating the encoding technique proposed solutions and solutions change depending on the shape of the recording. The article presents the general structure of the proposed hybrid approach. The description of the structure used fuzzy logic controller. The basic principles of fuzzy logic controller, describes the rules and mechanisms of the process of fuzzification / defuzzification solutions. To improve the efficiency of the fuzzy logic controller is proposed to use a multi-layer neural network. Marked the main differences of the proposed structure of the neural network of the "traditional" neural networks. To assess the quality of the decisions and the process of finding solutions to the general proposed to use the parameters characterizing the dynamics of the middle and the best value of the objective function, and the diversity of the population. For each parameter set the range of acceptable values. A brief description of the program and the results of its testing of the effectiveness of the proposed method. Shows the dependence of the probability of performing genetic operators on the values of the control parameters. The parameters of a fuzzy logic controller asked by default, as well as the type of membership functions of fuzzy sets.

Download PDF

Keywords Placement of circuit elements of electronic computing equipment; fuzzy genetic algorithm; artificial neural networks; evolutionary computation; hybrid intelligent methods.
References 1. Gladkov L.A., Kureychik V.M., Kureychik V.V., Sorokoletov P.V. Bioinspirirovannye metody v optimizatsii [Bioinspired methods in optimization]. Moscow: Fizmatlit, 2009, 384 p.
2. Gladkov L.A., Kureychik V.V., Kureychik V.M. Geneticheskie algoritmy [Genetic algorithms]. Moscow: Fizmatlit, 2010, 368 p.
3. Gladkov L.A., Kureychik V.V., Kureychik V.M., Rodzin S.I. Osnovy teorii evolyutsionnykh vychisleniy. Monografiya [Fundamentals of the theory of evolutionary computation. Monograph]. Rostov-on-Don: Izd-vo YuFU, 2010.
4. Kureychik V.V., Kureychik V.M., Rodzin S.I. Kontseptsiya evolyutsionnykh vychisleniy, inspirirovannykh prirodnymi sistemami [Concept evolutionary computation is inspired by natural systems], Izvestiya YuFU. Tekhnicheskie nauki [Izvestiya SFedU. Engineering Sciences], 2009, No. 4 (93), pp. 16-24.
5. Cohoon J.P., Karro J., Lienig J. Evolutionary Algorithms for the Physical Design of VLSI Circuits. Advances in Evolutionary Computing: Theory and Applications, Ghosh, A., Tsutsui, S. (eds.) Springer Verlag, London, 2003, pp. 683-712.
6. Charles J. Alpert, Dinesh P. Mehta, Sachin S. Sapatnekar. Handbook of algorithms for physical design automation. CRC Press, New York, USA, 2009.
7. Norenkov I.P. Osnovy avtomatizirovannogo proektirovaniya [Fundamentals of CAD]. Moscow: Izd-vo MGTU im. N.E. Baumana, 2006, 336 p.
8. Shervani N. Algorithms for VLSI physical design automation. USA, Kluwer Academy Publisher, 1995, 538 p.
9. Gladkov L.A. O nekotorykh podkhodakh k postroeniyu gibridnykh intellektual'nykh sistem dlya resheniya grafovykh zadach [Some approaches to the construction of hybrid intelligent systems for solving graph problems], Novosti iskusstvennogo intellekta [News of Artificial Intelligence], 2000, No. 3, pp. 71-90.
10. Kureychik V.M. Modifitsirovannye geneticheskie operatory [Modified genetic operators], Izvestiya YuFU. Tekhnicheskie nauki [Izvestiya SFedU. Engineering Sciences], 2009, No. 12 (101), pp. 7-15.
11. Mychalewicz Z. Genetic algorithms + data structures = evolution programs. Springer Verlag, 1996.
12. Herrera F., Lozano M. Fuzzy Adaptive Genetic Algorithms: design, taxonomy, and future directions, Soft Computing 7(2003), Springer-Verlag, 2003, pp. 545-562.
13. Herrera F., Lozano M. Adaptation of genetic algorithm parameters based on fuzzy logic controllers. In: F. Herrera, J.L. Verdegay (eds.) Genetic Algorithms and Soft Computing, Physica-Verlag, Heidelberg, 1996, pp. 95-124.
14. Kacprzyk J. Multistage control under fuzziness using genetic algorithms, Control and Cybernetics, Vol. 25, No. 6, pp. 1181-1216.
15. Yarushkina N.G. Osnovy teorii nechetkikh i gibridnykh system [Fundamentals of the theory of fuzzy and hybrid systems]. Moscow: Finansy i statistika, 2004, 320 p.
16. Batyrshin I.Z., Nedosekin A.O. i dr. Nechetkie gibridnye sistemy. Teoriya i praktika [Fuzzy hybrid system. Theory and practice], Under ed. N.G. Yarushkinoy. Moscow: Fizmatlit, 2007, 208 p.
17. Pegat A. Nechetkoe modelirovanie i upravlenie [Fuzzy modeling and control]. Moscow: BINOM. Laboratoriya znaniy, 2009, 798 p.
18. Borisov V.V., Kruglov V.V., Fedulov A.S. Nechetkie modeli i seti [Fuzzy models and networks]. Moscow: Goryachaya liniya – Telekom, 2007, 284 p.
19. Gladkov L.A. Integrirovannyy algoritm resheniya zadach razmeshcheniya i trassirovki na osnove nechetkikh geneticheskikh metodov [The integrated algorithm of the decision of problems of placement and routing on the basis of fuzzy genetic methods], Izvestiya YuFU. Tekhnicheskie nauki [Izvestiya SFedU. Engineering Sciences], 2011, No. 7 (120), pp. 22-30.
20. Gladkov L.A. Gibridnyy geneticheskiy algoritm resheniya zadachi razmeshcheniya elementov SBIS s uchetom trassiruemosti soedineniy [A hybrid genetic algorithm for solving the placement of elements VLSI traceability connections], Vestnik rostovskogo gosudarstvennogo universiteta putey soobshcheniya [Vestnik of Rostov State University of Railway Engineering], 2011, No. 3, pp. 58-66.

Comments are closed.