Development of a verification method of estimated indicators for their use as an optimization criterion

Authors

DOI:

https://doi.org/10.15587/1729-4061.2017.95914

Keywords:

local efficiency criterion, estimated indicators verification method, optimization criterion

Abstract

The optimization criterion is that reference point of the controlled systems, which provides the maximum coherence of the operational process results with the purpose of its owner. Difficulties of solving the tasks, connected with the choice of an adequate optimization criterion are caused by the fact that a large number of indicators intended for use as an optimization criterion have been developed and continue to be developed now.

The verification process of the indicator, which can potentially be used as an optimization criterion, is rather difficult. This difficulty is caused by the fact that the identification process is based on an exclusion method. Those indicators that have shown contradictory results on the classes of operations models identified by the rating efficiency should be excluded from the “contenders”.

During the researches, the hypothesis on the possibility of creating the reference models, allowing the development of direct verification methods wasn’t confirmed. However, the comparative research of cybernetic models of operations with different duration for consistency has allowed setting a restriction on the formation rules of models of this class and defining the rules of their equivalent converting.

Besides, during the researches, the method of creating a class of simple operation models with the predetermined identification, concerning their rating efficiency, has been developed. This means that the rating creation of these models doesn't require determination of local efficiency criteria.

Creation of a new class of reference models expands the possibilities of the estimated indicator verification method. At the same time, the positive effect of expansion of the opportunities of the verification method is shown not so much in an increase in the probability of excluding the inadequate estimated indicator, but in the introduction of a restriction on the rules of creating the classes of reference operation models.

Introduction of a restriction prevents the possibility of excluding the adequate estimated indicator from consideration.

Author Biographies

Igor Lutsenko, Kremenchuk Mykhailo Ostrohradskyi National University Pershotravneva str., 20, Kremenchuk, Ukraine, 39600

Doctor of Technical Sciences, Professor

Department of Electronic Devices 

 

Elena Fomovskaya, Kremenchuk Mykhailo Ostrohradskyi National University Pershotravneva str., 20, Kremenchuk, Ukraine, 39600

PhD, Associate Professor, Head of Department

Department of Electronic Devices

Iryna Oksanych, Kremenchuk Mykhailo Ostrohradskyi National University Pershotravneva str., 20, Kremenchuk, Ukraine, 39600

PhD, Associate Professor

Department of Information and Control Systems

Svetlana Koval, Kremenchuk Mykhailo Ostrohradskyi National University Pershotravneva str., 20, Kremenchuk, Ukraine, 39600

PhD, Senior Lecturer

Department of Information and Control Systems 

Olga Serdiuk, Kryvyi Rih National University Vitaliia Matusevycha str., 11, Kryvyi Rih, Ukraine, 50027

Postgraduate student

Department of computer systems and networks

References

  1. Lutsenko, I., Vihrova, E., Fomovskaya, E., Serdiuk, O. (2016). Development of the method for testing of efficiency criterion of models of simple target operations. Eastern-European Journal of Enterprise Technologies, 2 (4 (80)), 42–50. doi: 10.15587/1729-4061.2016.66307
  2. Lutsenko, I., Fomovskaya, E., Oksanych, I., Vikhrova, E., Serdiuk, О. (2017). Formal signs determination of efficiency assessment indicators for the operation with the distributed parameters. Eastern-European Journal of Enterprise Technologies, 1 (4 (85)), 24–30. doi: 10.15587/1729-4061.2017.91025
  3. Gorbatyuk, S. M., Shapoval, A. A., Mos’pan, D. V., Dragobetskii, V. V. (2016). Production of periodic bars by vibrational drawing. Steel in Translation, 46 (7), 474–478. doi: 10.3103/s096709121607007x
  4. Anishchenka, U. V., Kryuchkov, A. N., Kul’bak, L. I., Martinovich, T. S. (2008). Optimization of the structure of multifunctional information systems according to the criterion of a required value of the efficiency ratio. Automatic Control and Computer Sciences, 42 (4), 203–209. doi: 10.3103/s0146411608040068
  5. Miskowicz, M. (2010). Efficiency of Event-Based Sampling According to Error Energy Criterion. Sensors, 10 (3), 2242–2261. doi: 10.3390/s100302242
  6. Xu, Q., Wehrle, E., Baier, H. (2012). Adaptive surrogate-based design optimization with expected improvement used as infill criterion. Optimization, 61 (6), 661–684. doi: 10.1080/02331934.2011.644286
  7. Xia, L. (2016). Optimization of Markov decision processes under the variance criterion. Automatica, 73, 269–278. doi: 10.1016/j.automatica.2016.06.018
  8. Shapoval, A. A., Mos’pan, D. V., Dragobetskii, V. V. (2016). Ensuring High Performance Characteristics For Explosion-Welded Bimetals. Metallurgist, 60 (3-4), 313–317. doi: 10.1007/s11015-016-0292-9
  9. Vasilyev, E. S. (2013). Optimization of the architecture of a charge pump device on the basis of the energy efficiency criterion. Journal of Communications Technology and Electronics, 58 (1), 95–99. doi: 10.1134/s1064226913010099
  10. Shorikov, A. F., Rassadina, E. S. (2010). Multi-criterion optimization of production range generation by an enterprise. Economy of Region, 2, 189–196. doi: 10.17059/2010-2-18
  11. Dragobetskii, V. V., Shapoval, A. A., Mospan, D. V., Trotsko, O. V., Lotous, V. V. (2015). Excavator bucket teeth strengthening using a plastic explosive deformation. Metallurgical and Mining Industry, 4, 363–368.
  12. Mansour, M. R., Delbem, A. C. B., Alberto, L. F. C., Ramos, R. A. (2015). Integrating Hierarchical Clustering and Pareto-Efficiency to Preventive Controls Selection in Voltage Stability Assessment. Evolutionary Multi-Criterion Optimization, 487–497. doi: 10.1007/978-3-319-15892-1_33
  13. Harchenko, V. P., Babejchuk, D. G., Slyunyaev, O. S. (2009). Optimization of network information air navigation facilities by the generalized criterion of efficiency. Proceedings of National Aviation University, 38 (1), 3–5. doi: 10.18372/2306-1472.38.1650
  14. Yang, Q., Xu, J., Cao, B., Li, X.; Xu, J. (Ed.) (2017). A simplified fractional order impedance model and parameter identification method for lithium-ion batteries. PLOS ONE, 12 (2), e0172424. doi: 10.1371/journal.pone.0172424
  15. Malkov, M. V., Malyigina, S. N. (2010). Petri Nets and Modelling. Trudyi Kolskogo nauchnogo tsentra RAN, 3, 35–40.
  16. Lutsenko, I. (2015). Identification of target system operations. Development of global efficiency criterion of target operations. Eastern-European Journal of Enterprise Technologies, 2 (2 (74)), 35–40. doi: 10.15587/1729-4061.2015.38963

Downloads

Published

2017-04-24

How to Cite

Lutsenko, I., Fomovskaya, E., Oksanych, I., Koval, S., & Serdiuk, O. (2017). Development of a verification method of estimated indicators for their use as an optimization criterion. Eastern-European Journal of Enterprise Technologies, 2(4 (86), 17–23. https://doi.org/10.15587/1729-4061.2017.95914

Issue

Section

Mathematics and Cybernetics - applied aspects