RESEARCH OF MULTIPLE PLANS IN MULTI-FACTOR EXPERIMENTS WITH A MINIMUM NUMBER OF TRANSITIONS OF LEVELS OF FACTORS
DOI:
https://doi.org/10.15588/1607-3274-2019-2-6Keywords:
мethods, optimal experiment plan, set, software, costAbstract
Contex. The actual problem of reducing the set of plans for multivariate experiments in searching for the best in price costs hasbeen solved.
Objective is the synthesis and study of a variety of experimental plans with a minimum number of transitions of factor levels.
Methods. The use of experimental design methods allows reducing the price and time costs in the study of various technological
processes, devices and systems.
Minimizing the number of transitions of levels of factors in terms of the experiment, in turn, leads to a decrease in the cost (time)
of its implementation. One of the methods for reducing the number of transitions of levels of factors is the use of the Gray code when
constructing a plan of an experiment.
It is shown that multi-factor experiments plans constructed using the Gray code have a minimum number of transitions of factor
levels, but are not always optimal in terms of the cost (time) of the experiment.
For the synthesis of many experimental plans with a minimum number of transitions of levels of factors in searching for the optimal
plan for cost (time) costs, a method based on the generation of binary code variants is proposed. Analysis of their characteristics
and the choice of sequences that meet specified requirements were conducted. The formation of test plans for an experiment is
carried out according to the method based on the generation of variants for constructing plans, determining equivalence classes with
respect to a given group P of transformations and forming a set of typical representatives for the selected equivalence classes.
Results. Software that implements the proposed methods, which is used in the construction of a set of experimental plans for the
number of factors K = 3 with the minimum number of level transitions was developed.
Conclusions. The experiments, which were carried out, confirmed the efficiency of the proposed methods and the software implementing
them makes it possible to reduce the set of experiment plans for finding the optimal one. The scientific originality of the
research is presented by the methods which allow to synthesize many plans of multifactor experiments to reduce the search for optimal
plans in price (time) cost. The practical significance of the research results is in the developed software which implements the
proposed methods. It can be widely used in the study of technological processes, devices and systems, on which the implementation
of an active experiment is possible.
References
Koshevoj N. D., Koshevaja I. I., Kostenko E. M. Primenenie metodov optimizacii, osnovannyh na kode Greja, pri issledovanii
tehnologicheskih processov i priborov, Vіsnik Hersons’kogo nacіonal’nogo tehnіchnogo unіversitetu, 2018, No. 3,
Tom 2, pp. 241–245.
Hoskins D. S. Combinatorics and Statistical Inferecing. Applied Optimal Designs, vol.4, 2007, pp.147-179.
Morgan J. P. Association Schemes: Designed Experiments, Algebra and Combinatorics. Journal of the American Statistical
Association, 2005, Vol. 100, No. 471, pp. 1092–1093.
Bailey R. A., Cameron P. G. Combinatorics of optimal designs. Surveys in Combinatorics, Vol. 365, 2009, pp. 19–73.
Karpenko A. P. Sovremennye algoritmy poiskovoj optimizacii. Algoritmy, vdohnovlennye prirodoj: uchebnoe posobie. Moscow,
izd-vo MGTU im. N. Je Baumana, 2014, 446 p.
Koshevoj N. D., Kostenko E. M. Optimal’noe po stoimostnym i vremennym zatratam planirovanie jeksperimenta. Poltava, izdatel’ Shevchenko R. V., 2013, 317 p.
Montgomery D. C. Design and Analysis of Experiments, 9th ed. Wiley, 2017, 629 p.
Bartos B. J. Cleary R. Mc., Dowall D. Mc. Design and analysis of time series experiments. Oxford, Oxford University Press,
, 393 p.
Berger P. D., Maurer R. E. Experimental Design with Applications in Management, Engineering and the Sciences. Celli New
York, Springer, 2018, 640 p.
Rodrigues M. I., Iemma A. F. Experimental Design and Process Optimization. N.-Y., CRC Press, 2016, 336 p.
Wu C. F. J., Hamada M. S. Experiments: Planning, Analysis, and Optimization. Wiley, 2015, 743 p.
Koshevoj N. D., Beljaeva A. A. Primenenie algoritma optimizacii roem chastic dlja minimizacii stoimosti provedenija
mnogofaktornogo jeksperimenta, Radio Electronics, Computer Science, Control, 2018, No. 1, pp. 41–49. DOI 10.15588/1607-
-2018-1-5.
Koshevoj N. D., Beljaeva A. A. Sravnitel’nyj analiz metodov optimizacii pri issledovanii vesoizmeritel’noj sistemy i
termoreguljatora, Radio Electronics, Computer Science, Control, 2018, №4, pp. 179–187. DOI: 10. 15588/1607-3274-2018-
-17. DOI:
Gal’chenko V. Ja., Trembovec’ka R. V., Tuchkov V. V. Zastosuvannja nejrokomp’jutinga na etapі pobudovi metamodelej v
procesі optimal’nogo surogatnogo sintezu anten, Visnyk NTUU KPI: Seriia Radiotekhnika Radioaparatobuduvannia, 2018, Issue
, pp. 60–72. DOI: 10.20535/RADAP.2018.74.60-72.
Yakovlev S. Convex extensions in combinatorial optimization and their applications, Springer Optimization and its Applications.
New York, Springer, 2017, Vol. 130, pp. 567–584.
Yakovlev S. V., Pichugina O. S. Properties of combinatorial optimization problems over polyhedral-spherical sets, Cybernetics
and Systems Analysis, 2018, No. 1, Vol. 54, pp. 99–109.
Ugryumov M. L., Men’shikov V. A., Belik V. V. Networkcharacteristic calculation method of spatial boundary layer on
bounding surface of interblade channel of turboset, Izvestiya Vysshikh Uchebnykh Zavedenij. Aviatsionnaya Tekhnika, 1992,
No. 1, pp. 38–41.
Ugryumov M. L.. Afanasjevska V. E., Tronchuk A. A. , Myenyaylov A. V. Stochastic optimization models and method
in the turbomachines system improvement problem, ASMEJSME-KSME 2011 Joint Fluids Engineering Conference, AJK,
, No. 1 (PARTS A, B, C, D), pp. 755–761.
Koshovy`j M. D., Koshova I. I., Dergachov V. A., Pavlyk G. V., Kostenko O. M. Komp’yuterna programa “Programa
formuvannya variantiv kodiv z minimal`ny`my` zminamy`”, svid. pro reyestr. avtor. prava na tvir №74877, Zareyestr.
v Ministerstvi ekonomichnogo rozvy`tku i torgivli Ukrayiny` 21.11.2017r.
Koshovy`j M. D., Koshova I. I., Dergachov V. A., Pavly`k G. V. , Kostenko O. M. Komp’yuterna programa «Programa
formuvannya ty`povy`x planiv bagatofaktornogo ekspery`mentu», svid. pro reyestr. avtor. prava na tvir №74881.
Zareyestr v Ministerstvi ekonomichnogo rozvy`tku i torgivli Ukrayiny` 21.11.2017r.
Firsov S. N., Reznikova O. V. Apparatno-programmnyj kompleks jeksperimental’noj otrabotki processov upravlenija, diagnostirovanija i parirovanija otkazov malyh kosmicheskih apparatov, Pribory i sistemy. Upravlenie, kontrol’, diagnostika,
, No. 6, pp. 60–69. eLIBRARY ID: 22776434.
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