APPLICATION OF THE FISH SEARСH METHOD FOR OPTIMIZATION PLANS OF THE FULL FACTOR EXPERIMENT

Authors

  • N. D. Koshevoy National Aerospace University named after N. Ye. Zhukovsky “Kharkiv aviation institute”, Kharkiv, Ukraine
  • E. M. Kostenko Poltava State Agrarian Academy, Poltava, Ukraine
  • V. V. Muratov National Aerospace University named after N. Ye. Zhukovsky “Kharkiv aviation institute”, Kharkiv, Ukraine

DOI:

https://doi.org/10.15588/1607-3274-2020-2-5

Keywords:

Оptimal plan, search by school of fish, optimization, experiment planning, cost, win.

Abstract

Context. An application of the method of searching for schools of fish to construct optimal experiment plans for cost (time) in the study of technological processes and systems that allow the implementation of an active experiment on them is proposed.

Object of study. Optimization methods for cost (time) costs of experimental designs, based on the application of a school of fish search algorithm.

Objective. To obtain optimization results by optimizing the search for schools of fish for the cost (time) costs of plans for a full factorial experiment.

Method. A method is proposed for constructing a cost-effective (time) implementation of an experiment planning matrix using algorithms for searching for schools of fish. At the beginning, the number of factors and the cost of transitions for each factor level are entered. Then, taking into account the entered data, the initial experiment planning matrix is formed. The school of fish search method is based on the rearrangement of the columns of the experiment planning matrix, based on the sum of the costs (times) of transitions between levels for each of the factors. Fish schools are formed according to the following principle: fewer schools of fish where the sum of the costs (times) of transitions between levels of factors is greater. Then, rearrangements of schools of fish located nearby in the experiment planning matrix are performed. Then the gain is calculated in comparison with the initial cost (time) of the experiment.

Results. Software has been developed that implements the proposed method, which was used to conduct computational experiments to study the properties of these methods in the study of technological processes and systems that allow the implementation of an active experiment on them. The experimental designs that are optimal in terms of cost (time) are obtained, and the winnings in the optimization results are compared with the initial cost of the experiment. A comparative analysis of optimization methods for the cost (time) costs of plans for a full factorial experiment is carried out.

Conclusions. The conducted experiments confirmed the operability of the proposed method and the software that implements it, and also allows us to recommend it for practical use in constructing optimal experiment planning matrices.

Author Biographies

N. D. Koshevoy, National Aerospace University named after N. Ye. Zhukovsky “Kharkiv aviation institute”, Kharkiv

Dr. Sc., Professor, Head of the Department of Intelligent Measuring Systems and Quality Engineering

E. M. Kostenko, Poltava State Agrarian Academy, Poltava

Dr. Sc., Professor, Vice-rector

V. V. Muratov, National Aerospace University named after N. Ye. Zhukovsky “Kharkiv aviation institute”, Kharkiv

Postgraduate student of the Department of Intellectual Measuring Systems and Quality Engineering

References

Koshevoj N. D., Kostenko E. M. Optimal’noe po stoimostnym I vremennym zatratam planirovanie jeksperimenta. Poltava, izdatel’ Shevchenko R. V., 2013, 317 p.

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 eksperymentu», svid. pro reyestr. avtor. prava na tvir No74881. Zareyestr v Ministerstvi ekonomichnogo rozvy`tku i torgivli Ukrayiny` 21.11.2017.

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, 2009, Vol. 365, pp. 19–73.

Koshevoj N. D., Beljaeva A. A. Sravnitel’nyj analiz metodov optimizacii pri issledovanii vesoizmeritel’noj sistemy i termoreguljatora, Radio Electronics, Computer Science, Control, 2018, No4, pp. 179–187. DOI: 10. 15588/16073274-2018-4-17.

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 10.15588/1607-3274-2018-1-5.

Koshevoy N. D. The study of many plans for multifactor experiments with a minimum number of transitions of factor levels, Radio electronics, informatics, control, 2019, No. 2, pp. 53–59.

Koshevoy N. D., Kostenko E. M., Pavlik A. V. and others. The methodology of the optimal planning for the cost and time of experiment planning, monograph. Poltava, Poltava State Agrarian Academy, 2017, 232 p.

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 74, pp. 60–72. DOI: 10.20535/RADAP.2018.74.60-72.

Rodrigues M. I., Iemma A. F. Experimental Design and Process Optimization. N.-Y., CRC Press, 2016, 336 p.

Yakovlev S. Convex extensions in combinatorial optimization and their, Springer Optimization and its Applications. Springer, New York, 2017, Vol. 130, pp. 567–584.

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, 2014, No. 6, pp. 60–69. eLIBRARY ID: 22776434.

Bartos B. J. Cleary R. Mc., Dowall D. Mc. Design and analysis of time series experiments. Oxford, Oxford University Press, 2017, 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.

Karpenko A. P. Sovremennye algoritmy poiskovoj optimizacii. Algoritmy, vdohnovlennye prirodoj: uchebnoe posobie. Moscow, izd-vo MGTU im. N. Je Baumana, 2014, 446 p.

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.

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How to Cite

Koshevoy, N. D., Kostenko, E. M., & Muratov, V. V. (2020). APPLICATION OF THE FISH SEARСH METHOD FOR OPTIMIZATION PLANS OF THE FULL FACTOR EXPERIMENT. Radio Electronics, Computer Science, Control, (2), 44–50. https://doi.org/10.15588/1607-3274-2020-2-5

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Section

Mathematical and computer modelling

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