Skip to main content

Intuitionistic Fuzzy Sets for Estimating the Parameters of Distributive Task

  • Conference paper
  • First Online:
13th International Conference on Theory and Application of Fuzzy Systems and Soft Computing — ICAFS-2018 (ICAFS 2018)

Abstract

This article proposes an approach to assessing factors that affect the solution of distribution problems. Distribution tasks are widely used at present. The system principle of investigating the objects of the distribution system corresponds to the understanding that when studying them it is necessary to start from internal connections and multilateral interdependencies between a large number of elements. The increase of the system parameters allows to optimize complex resource allocation problems and to take into account a greater number of factors affecting the final result. One of the important parameters of the distribution system is demand. A correct definition of the magnitude of demand affects the solution of several problems: planning and organization of production procedure; calculation of optimal levels of orders for resources, as well as the determination of volumes and the rational functioning of the transport subsystem. Since the total number of factors influencing the level of demand is very high, an expert needs a tool to distinguish groups of such factors. In order to solve this problem it is proposed to use intuitionistic fuzzy sets, which allow to take into consideration the influence degree of factors on the controlled parameter. This approach allows a large number of unordered factors to be converted into a small number of significant and agreed factors, which can provide the basis for a visual and informative analysis.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Schenk, M., Tolujew, J., Reggelin, T.: A mesoscopic approach to the simulation of logistics systems. In: Advanced Manufacturing and Sustainable Logistics, pp. 15–25. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  2. Giraud, L., Bavière, R., Vallée, M., Paulus, C.: Recent advances in modelling, simulation and operational optimization of DH systems. Euroheat and Power (English Edition) 13(4), 12–15 (2016)

    Google Scholar 

  3. Muckstadt, J., Sapra, A.: Principles of Inventory Management. When You Are Down to Four Order More. Springer Series in Operations Research and Financial Engineering. Springer, New York (2010)

    Book  Google Scholar 

  4. Brandimarte, P., Zotteri, G.: Introduction to Distribution Logistics. Wiley, Hoboken (2007)

    Book  Google Scholar 

  5. Gudehus, T., Kotzab, H.: Comprehensive Logistics. Springer, Heidelberg (2012)

    Book  Google Scholar 

  6. Wardlow, D., Wood, D., Johnson, P.: Modern logistic. Murphy. Trudged., Publ. house Williams (2002)

    Google Scholar 

  7. Rushton, A., Croucher, P., Baker, P.: The Handbook of Logistics and Distribution Management: Understanding the Supply Chain. Kogan Page, London (2014)

    Google Scholar 

  8. Du, D.-Z., Ko, K.I., Hu, X.: Design and Analysis of Approximation Algorithms. Springer, Heidelberg (2012)

    Book  Google Scholar 

  9. Kuzmin, E.: Uncertainty and Certainty in Management of Organizational-Economic Systems. LAP LAMBERT Academic Publishing, Munich (2012)

    Google Scholar 

  10. Mac Queen, J.: Some methods for classification and analysis of multivariate observations. In: Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability, pp. 281–297 (1967)

    Google Scholar 

  11. Lambert, D., Stock, J., Ellram, L.: Fundamentals of Logistics Management. McGraw-Hill/Irwin, New York (1997)

    Google Scholar 

  12. Ross, D.: Introduction to Supply Chain Management Technologies. CRC Press, Boca Raton (2010)

    Google Scholar 

  13. Seraya, O.: Mnogomernye modeli logistiki v usloviyah neopredelennosti. FOP Stecenko I. I., Kharkiv (2010)

    Google Scholar 

  14. Kosenko, O., Sinyavskaya, E., Shestova, E., Kosenko, E., Chemes, O.: Method for solution of the multi-index transportation problems with fuzzy parameters. In: XIX IEEE International Conference on Soft Computing and Measurements (SCM), pp. 179–182 (2016)

    Google Scholar 

  15. Kosenko, O., Shestova, E., Sinyavskaya, E., Kosenko, E., Nomerchuk, A., Bozhenyuk, A.: Development of information support for the rational placement of intermediate distribution centers of fuel and energy resources under conditions of partial uncertainty. In: XX IEEE International Conference on Soft Computing and Measurements (SCM), pp. 224–227 (2017)

    Google Scholar 

  16. Dubois, D., Prade, H.: Fuzzy Sets and Systems. Academic Press, New York (1980)

    MATH  Google Scholar 

  17. Raskin, L., Seraya O.: Nechetkaya matematika. Osnovy teorii. Prilozheniya. Parus, Kharkiv (2008)

    Google Scholar 

  18. Atanassov, K.: On Intuitionistic Fuzzy Sets Theory. Springer, New York (2012)

    Book  Google Scholar 

  19. Atanassov, K.: New operations defined over the intuitionistic fuzzy sets. Fuzzy Sets Syst. 61(2), 137–142 (1994)

    Article  MathSciNet  Google Scholar 

  20. Shabir, M., Khan, A.: Intuitionistic fuzzy filters of ordered semigroups. J. Appl. Math. Inform. 26(5–6), 213–220 (2008)

    MATH  Google Scholar 

  21. Pagurova, V.: A limiting multidimensional distribution of intermediate order statistics. Mosc. Univ. Comput. Math. Cybern. 41(3), 130–133 (2017)

    Article  MathSciNet  Google Scholar 

Download references

Acknowledgments

This work has been supported by the Russian Foundation for Basic Research, Project № 18-01-00023a.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Alexander Bozhenyuk .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Bozhenyuk, A., Knyazeva, M., Kosenko, O. (2019). Intuitionistic Fuzzy Sets for Estimating the Parameters of Distributive Task. In: Aliev, R., Kacprzyk, J., Pedrycz, W., Jamshidi, M., Sadikoglu, F. (eds) 13th International Conference on Theory and Application of Fuzzy Systems and Soft Computing — ICAFS-2018. ICAFS 2018. Advances in Intelligent Systems and Computing, vol 896. Springer, Cham. https://doi.org/10.1007/978-3-030-04164-9_25

Download citation

Publish with us

Policies and ethics