University of Cadiz
Krasnoyarsk, Russian Federation
Russian Federation
Puerto-Real', Spain
University of Cadiz
Krasnoyarsk, Russian Federation
The authors applied the Data Envelopment Analysis (DEA) to assess the performance of the heat supply system in the city of Krasnoyarsk. The article provides a detailed description of the DEA method, its positive sides and shortcomings. The research included a comparative analysis of performance assessment methods in terms of advantages and disadvantages. The DEA method proved the most convenient tool for measuring the production efficiency of an object. The authors modified the architecture of the universal decision support system into a DEA-based one. The DEA method also proved highly efficient in assessing the performance of the heat supply system in the city of Krasnoyarsk. The analysis made it possible to develop recommendations to improve the efficiency of the local heat supply system using the case of thirteen unites, e.g. boilers, heat and power plants, etc. The input indicator was represented by the available heat capacity. Heat output to the grid and emission mass were used as output indicators. Based on the available initial data, the authors constructed an output-oriented model for analyzing the functioning environment with one input and two outputs. They identified inefficient units of the Krasnoyarsk heat supply system and proposed optimization of input and output values for each unit to improve the functioning of the heat supply system as a whole. The developed for the upgrading of boilers and heat and power plants had an efficiency index in the range up to 1.
decision support system, model, decision module, linear programming, heat supply system, level of harmful substances emitted, heat output, heat energy supply to the network, mass of emission, environment
1. Morgunov E. P., Morgunova O. N. Formation of an artificial border of efficiency in the Data Envelopment Analysis method. Bulletin of the Reshetnev Siberian State Aerospace University, ed. Beliakov G. P. Krasnoyarsk: SibGAU, 2003, 385-386. (In Russ.)
2. Cooper W. W., Seiford L. M., Tone K. Data Envelopment Analysis. Boston: Kluwer Academic Publishers, 2000, 318. DOI:https://doi.org/10.1007/b109347
3. Shugaley A. P., Chevtaeva V. V., Dolganova A. A. Application of the Data Envelopment Analysis method for measuring of efficiency of departments of medical institution. Reshetnevsky Readings, 2018, 2: 372-373. (In Russ.)
4. Emrouznejad A. R., Yang G. A survey and analysis of the first 40 years of scholarly literature in DEA: 1978-2016. Socio-Economic Planning Sciences, 2018, 61: 4-8. DOI: https://doi.org/10.1016/j.seps.2017.01.008
5. Morgunov E. P. Decision support system for efficiency assessment of complex systems: design principles, requirements and architecture. Vestnik SibGAU, 2007, (3): 59-63. (In Russ.)
6. Emrouznejad A. R., Banker R., Lopes A. L. M., Almeida M. Data Envelopment Analysis in the public sector. Socio-Economic Planning Sciences, 2014, 48(1): 2-3. DOI:https://doi.org/10.1016/j.seps.2013.12.005
7. Morgunova O. N. The information system as a data source for assessing the level of efficiency of objects and processes in the field of higher education. Theoretical and applied issues of modern information technologies: Proc. VI All-Russian Sci.-Techn. Conf., Ulan-Ude, July 25-31, 2005. Ulan-Ude, 2005, pt. 2, 286-289. (In Russ.)
8. Kovalev I. V., Karaseva M. V. Multilinguistic technologies of preparation and decision-making in distributed information and control systems. Krasnoyarsk: SibGAU, 2010, 132. (In Russ.)
9. Ruiga I. R., Stupina A. A. Assessment of innovation and investment the sustainability of socio-economic systems based on methods of system analysis: theoretical aspect. Digital economy and industry 4.0: trends 2025: Proc. Sci.-Prac. Conf. with Intern. participation, St. Petersburg, April 3-5, 2019. St. Petersburg, 2019, 201-209. (In Russ.) DOI:https://doi.org/10.18720/IEP/2019.1/29
10. Kuzmich R. I., Stupina A. A., Korpacheva L. N., Ezhemanskaja S. N., Ruiga I. R. The modified method of logical analysis used for solving classification problems. Informatica, 2018, 29(3): 467-486. DOI: http://dx.doi.org/10.15388/Informatica.2018.176
11. Morgunova O. N. The issue of performance assessment of complex hierarchical systems. System analysis in design and management: Proc. IX Intern. Sci.-Prac. Conf., St. Petersburg, June 30 - July 8, 2005. St. Petersburg, 2005, 48-53. (In Russ.)
12. Foroughi A. A., Shureshjani R. A. Solving generalized fuzzy data envelopment analysis model: a parametric approach. Cent. Eur. J. Oper. Res., 2017, 25: 889-905. DOI: https://doi.org/10.1007/s10100-016-0448-5
13. Tsarev R. Yu., Volkov V. A., Lokhmakov P. M. Software and information technologies for improving the reliability of control systems. Innovative resources of the Kuznetsk basin. IT-technologies: Proc. VI All-Russian Sci.-Prac. Conf., Kemerovo, March 19-21, 2007. Kemerovo, 2007, 63-66. (In Russ.)
14. Ruiga I. R., Stupina A. A., Kovzunova E. S., Chayka A. A., Shkradyuk I. A. Practical implementation of Data Envelopment Analysis technology to assess the innovative sustainability of resource-type regions. Journal Physics: Conference Series, 2019, 1399(3). DOI: doihttps://doi.org/10.1088/1742-6596/1399/3/033118
15. Chernyshova G. Yu., Kovalev R. N. Application of the Data Envelopment Analysis model for the web-resources efficiency. Fundamentalnye issledovaniia, 2017, (8-2): 453-457. (In Russ.)
16. Pokushko M. V., Stupina A. A., Medina-Bulo I., Dresvianskii E. S., Karaseva M. V. Application of data envelopment analysis method for assessment of performance of enterprises in fuel and energy complex. Journal of Physics: Conference Series, 2019, 1353. DOI:https://doi.org/10.1088/1742-6596/1353/1/012140
17. Widiarto I., Emrouznejad A. Social and financial efficiency of Islamic microfinance institutions: a Data Envelopment Analysis application. Socio-Economic Planning Sciences, 2015, 50: 1-17. DOI: https://doi.org/10.1016/j.seps.2014.12.001
18. Antamoshkin A. N., Morgunova O. N., Morgunov E. P. Efficiency assessment technique for complex hierarchical systems. Vestnik SibGAU, 2006, (2): 9-13. (In Russ.)
19. Ruiga I. R. The possibilitiy of using the Data Envelopment Analysis method to estimate the region innovative stability. Reshetnevsky Readings, 2017, 2: 452-453. (In Russ.)
20. Jablonsky J. Efficiency analysis in multi-period systems: an application to performance evaluation in Czech higher education. Cent. Eur. J. Oper. Res., 2016, 24: 283-296. DOI: https://doi.org/10.1007/s10100-015-0401-z
21. Roháčová V. A DEA based approach for optimization of urban public transport system. Cent. Eur. J. Oper. Res., 2015, 23: 215-233. DOI: https://doi.org/10.1007/s10100-013-0314-7
22. Ruiga I. R., Zemlyanko M. P. Foreign experience of using digital technologies in the city's strategic development. Digital economy and Industry 4.0: new challenges: Proc. Sci.-Prac. Conf. with Intern. participation, St. Petersburg, April 2-4, 2018. St. Petersburg, 2018, 217-225. (In Russ.) DOI:https://doi.org/10.18720/IEP/2018.1/29
23. Takano Y., Ishii N., Muraki M. Multi-period resource allocation for estimating project costs in competitive bidding. Cent. Eur. J. Oper. Res., 2017, 25: 303-323. DOI: https://doi.org/10.1007/s10100-016-0438-7
24. Branda M., Kopa M. On relations between DEA-risk models and stochastic dominance efficiency tests. Cent. Eur. J. Oper. Res., 2014, 22: 13-35. DOI: https://doi.org/10.1007/s10100-012-0283-2
25. Burenok V. M., Lavrinov G. A., Khrustalev E. Iu. Mechanisms for managing production of military products. Moscow: Nauka, 2006, 303. (In Russ.)
26. Morgunov E. P., Morgunova O. N. Promotion of the method of performance assessment of the Data Envelope Analysis systems in Russia. System analysis in design and management: Proc. XX Intern. Sci.-Prac. Conf., St. Petersburg, June 29 - July 1, 2016. St. Petersburg, 2016, 390-398. (In Russ.)
27. Krivonozhko V. E., Lychev A. V. An analysis of the activities of complex socio-economic systems. Moscow: MAKS Press, 2010, 207. (In Russ.)
28. Bussofiane A., Dyson R. G., Thanassoulis E. Applied data envelopment analysis. Rossiiskii zhurnal menedzhmenta, 2012, 10(2): 63-88. (In Russ.)
29. Fedotov Yu. V. Measuring organization performance: features of the DEA method (Data Envelopment Analysis). Rossiiskii zhurnal menedzhmenta, 2012, 10(2): 51-62. (In Russ.)
30. Morgunov E. P. Multidimensional classification based on the analytical method of evaluating the effectiveness of complex systems. Cand. Tech. Sci. Diss. Krasnoyarsk, 2003, 160. (In Russ.)
31. Lungu K. N. Linear programming. Guide to solving problems. Moscow: Fizmatlit, 2005, 126. (In Russ.)
32. Porunov A. N. The comparative effectiveness of public management environmental security in the region by dea-analysis (for example Volga federal district). Nauchnyi zhurnal NIU ITMO. Seriya: Ekonomika i ekologicheskii menedzhment, 2016, (1): 104-111. (In Russ.) DOI:https://doi.org/10.17586/2310-1172-2016-9-1-104-111
33. Morgunova O. N., Morgunov E. P. Computer support for decision-making on evaluating the effectiveness of the University's functioning. IT-innovations in education: Proc. All-Russian Sci.-Prac. Conf., Petrozavodsk, June 27-30, 2005. Petrozavodsk, 2005, 152-154. (In Russ.)
34. Petukhov G. B., Iakunin V. I. Methodological foundations of external design of purposeful processes and purposeful systems. Moscow: AST, 2006, 504. (In Russ.)
35. Prangishvili I. V. System approach and improvement of management efficiency. Moscow: Nauka, 2005, 420. (In Russ.)