Issue:Intuitionistic fully fuzzy balanced transportation problem

From Ifigenia, the wiki for intuitionistic fuzzy sets and generalized nets
Jump to: navigation, search
shortcut
http://ifigenia.org/wiki/issue:nifs/26/1/69-80
Title of paper: Intuitionistic fully fuzzy balanced transportation problem
Author(s):
Mohamed El Alaoui
Department of production and industrial engineering, ENSAM, Moulay Ismail University, Meknes, Morocco
mohamedelalaoui208At sign.pnggmail.com
Published in: Notes on Intuitionistic Fuzzy Sets, Volume 26 (2020), Number 1, pages 69–80
DOI: https://doi.org/10.7546/nifs.2020.26.1.69-80
Download: Download-icon.png PDF (611  Kb, Info) Download-icon.png
Abstract: This paper treats the balanced transportation problem in which uncertain demands, supplies and costs, are modeled by intuitionistic fuzzy numbers. The problem is transformed into

its crisp equivalent in order to be resolved. A comparison with recent methods is developed.

Keywords: Intuitionistic fuzzy number, Balanced transportation problem, Fully fuzzy.
AMS Classification: 03E72, 90B06, 90C70.
References:
  1. Abhishekh, B. & Nishad, A. K. (2018). A Novel Ranking Approach to Solving Fully LR-Intuitionistic Fuzzy Transportation Problems, New Math. Nat. Comput., 15 (1), 95–112.
  2. Aggarwal, S., & Gupta, C. (2016). Solving Intuitionistic Fuzzy Solid Transportation Problem Via New Ranking Method Based on Signed Distance, Int. J. Uncertain. Fuzziness Knowl.-Based Syst., 24 (4), 483–501.
  3. Aggarwal, S., & Gupta, C. (2017). Sensitivity Analysis of Intuitionistic Fuzzy Solid Transportation Problem, Int. J. Fuzzy Syst., 19 (6), 1904–1915.
  4. Atanassov, K. T. (1986). Intuitionistic fuzzy sets, Fuzzy Sets Syst., 20 (1), 87–96.
  5. Atanassov, K. T. (1999). Intuitionistic Fuzzy Sets: Theory and Applications. Physica-Verlag Heidelberg.
  6. Atanassov, K. T. (2014). Index Matrices: Towards an Augmented Matrix Calculus.Springer International Publishing, Cham.
  7. Atanassova, V., & Sotirov, S. (2012). A new formula for de-i-fuzzification of intuitionistic fuzzy sets, Notes on Intuitionistic Fuzzy Sets, 18 (3), 49–51.
  8. Ban, A., Kacprzyk, J., & Atanassov, K. (2008). On de-I-fuzzification of intuitionistic fuzzy sets, Comptes Rendus L’Academie Bulg. Sci., 61 (12), 1535–1540.
  9. Baykasoǧlu, A., & Göçken, T. (2008). A review and classification of fuzzy mathematical programs, J. Intell. Fuzzy Syst., 19 (3), 205–229.
  10. Bharati, S. K., & Malhotra, R. (2017). Two stage intuitionistic fuzzy time minimizing transportation problem based on generalized Zadeh’s extension principle, Int. J. Syst. Assur. Eng. Manag., 8 (2), 1442–1449.
  11. Bharati, S. K., & Singh, S. R. (2018). Transportation Problem Under Interval-Valued Intuitionistic Fuzzy Environment, Int. J. Fuzzy Syst., 20 (5), 1511–1522.
  12. Chakraborty, D., Jana, D. K., & Roy, T. K. (2015). Arithmetic operations on generalized intuitionistic fuzzy number and its applications to transportation problem, OPSEARCH, 52 (3), 431–471.
  13. Chakraborty, D., Jana, D. K., & Roy, T. K. (2016). A new approach to solve fully fuzzy transportation problem using triangular fuzzy number, Int. J. Oper. Res., 26 (2), 153–179.
  14. Chakraborty, D., Jana, D. K., & Roy, T. K. (2016). Expected value of intuitionistic fuzzy number and its application to solve multi-objective multi-item solid transportation problem for damageable items in intuitionistic fuzzy environment, J. Intell. Fuzzy Syst., 30 (2), 1109–1122.
  15. Ebrahimnejad, A., & Verdegay, J. L. (2017). A new approach for solving fully intuitionistic fuzzy transportation problems, Fuzzy Optim. Decis. Mak., 1–28.
  16. Ebrahimnejad, A., & Verdegay, J. L. (2018). MOLP Approach for Solving Transportation Problems with Intuitionistic Fuzzy Costs, in Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications, 319–329.
  17. El Alaoui, M. (2018). SMART Grid Evaluation Using Fuzzy Numbers and TOPSIS, IOP Conf. Ser. Mater. Sci. Eng., 353 (1), 12–19.
  18. El Alaoui, M., & Ben-azza, H. (2017). Aggregation of performance indicators for supply chain and fuzzy logic extensions applied to green supply chain, in 2017 International Colloquium on Logistics and Supply Chain Management (LOGISTIQUA), 36–41.
  19. El Alaoui, M., & Ben-azza, H. (2017). Generalization of the weighted product aggregation applied to data fusion of intuitionistic fuzzy quantities, in 2017 Intelligent Systems and Computer Vision (ISCV), 1–6.
  20. El Alaoui, M., Ben-azza, H. & El Yassini, K. (2018). Optimal weighting method for fuzzy opinions, Proc. of International Conference on Industrial Engineering and Operations Management, Paris, France, 2225–2230.
  21. El Alaoui, M., Ben-azza, H., & El Yassini, K. (2018). Optimal weighting method for interval-valued intuitionistic fuzzy opinions, Notes on Intuitionistic Fuzzy Sets, 24 (3), 106–110.
  22. El Alaoui, M., Ben-azza, H. & El Yassini, K. (2019). Achieving consensus in interval valued intuitionistic fuzzy environment, Procedia Comput. Sci., 148, 218–225.
  23. El Alaoui, M., Ben-azza, H. & Zahi, A. (2016). New Multi-criteria Decision-Making Based on Fuzzy Similarity, Distance and Ranking, in Proceedings of the Third International Afro-European Conference for Industrial Advancement — AECIA 2016, Springer, Cham, 138–148.
  24. El Alaoui, M., & El Yassini, K. (2020). Fuzzy Similarity Relations in Decision Making, Handb. Res. Emerg. Appl. Fuzzy Algebr. Struct., 369–385.
  25. El Alaoui, M., El Yassini, K., & Ben-azza, H. (2018). Enhancing MOOCs Peer Reviews Validity and Reliability by a Fuzzy Coherence Measure, in Proceedings of the 3rd International Conference on Smart City Applications, New York, NY, USA, 57:1–57:5.
  26. El Alaoui, M., El Yassini, K., & Ben-azza, H. (2019). Peer Assessment Improvement Using Fuzzy Logic, in Innovations in Smart Cities Applications, Edition 2, 408–418.
  27. El Alaoui, M., El Yassini, K., & Ben-azza, H. (2019). Type 2 fuzzy TOPSIS for agriculture MCDM problems, Int. J. Sustain. Agric. Manag. Inform., 5 (2/3), 112–130.
  28. Grzegorzewski, P., & Mrówka, E. (2005). Trapezoidal approximations of fuzzy numbers, Fuzzy Sets Syst., 153 (1), 115–135.
  29. Grzegorzewski, P., & Mrówka, E. (2007). Trapezoidal approximations of fuzzy numbers—revisited, Fuzzy Sets Syst., 158 (7), 757–768.
  30. Gupta, G., & Anupum, K. (2017). An Efficient Method for Solving Intuitionistic Fuzzy Transportation Problem of Type-2, Int. J. Appl. Comput. Math., 3 (4), 3795–3804.
  31. Hitchcock, F. L. (1941). The Distribution of a Product from Several Sources to Numerous Localities, J. Math. Phys., 20 (1–4), 224–230.
  32. Hunwisai, D., Kumam, P., & Kumam, W. (2018). A Method for Optimal Solution of Intuitionistic Fuzzy Transportation Problems via Centroid, in Econometrics for Financial Applications, 94–114.
  33. Jana, D. K. (2016). Novel arithmetic operations on type-2 intuitionistic fuzzy and its applications to transportation problem, Pac. Sci. Rev. Nat. Sci. Eng., 18 (3), 178–189.
  34. Kour, D., Mukherjee, S., & Basu, K. (2017). Solving intuitionistic fuzzy transportation problem using linear programming, Int. J. Syst. Assur. Eng. Manag., 8 (2), 1090–1101.
  35. Kumar, P. S. (2018). Linear Programming Approach for Solving Balanced and Unbalanced Intuitionistic Fuzzy Transportation Problems, Int. J. Oper. Res. Inf. Syst. IJORIS, 9 (2), 73–100.
  36. Kumar, P. S., & Hussain, R. J. (2016). Computationally simple approach for solving fully intuitionistic fuzzy real life transportation problems, Int. J. Syst. Assur. Eng. Manag., 7 (1), 90–101.
  37. Mahmoodirad, A., Allahviranloo, T., & Niroomand, S. (2019). A new effective solution method for fully intuitionistic fuzzy transportation problem, Soft Comput., 23, 4521–4530.
  38. Rani, D., & Gulati, T. R. (2016). Application of intuitionistic fuzzy optimization technique in transportation models, OPSEARCH, 53 (4), 761–777.
  39. Roy, S. K., Ebrahimnejad, A., Verdegay, J. L., & Das, S. (2018). New approach for solving intuitionistic fuzzy multi-objective transportation problem, Sādhanā, 43 (3), DOI:10.1007/s12046-017-0777-7.
  40. Singh, S. K., & Yadav, S. P. (2015). Efficient approach for solving type-1 intuitionistic fuzzy transportation problem, Int. J. Syst. Assur. Eng. Manag., 6 (3), 259–267.
  41. Singh, S. K., & Yadav, S. P. (2016). A new approach for solving intuitionistic fuzzy transportation problem of type-2, Ann. Oper. Res., 243 (1), 349–363.
  42. Singh, S. K., & Yadav, S. P. (2016). A novel approach for solving fully intuitionistic fuzzy transportation problem, Int. J. Oper. Res., 26 (4), 460–472.
  43. Singh, S. K. & Yadav, S. P. (2016). Intuitionistic fuzzy transportation problem with various kinds of uncertainties in parameters and variables, Int. J. Syst. Assur. Eng. Manag., 7 (3), 262–272.
  44. Traneva, V., Marinov, P., & Atanassov, K. (2016). Index matrix interpretations of a new transportation-type problem, Comptes Rendus Academie Bulg. Sci., 69 (10), 1275–1283.
  45. Traneva, V., Marinov, P., & Atanassov, K. (2016). Transportation-type problems and their index matrix interpretations, Adv. Stud. Contemp. Math., 26 (4), 587–594.
  46. Zadeh, L. A. (1965). Fuzzy sets, Inf. Control, 8 (3), 338–353.
  47. Zimmermann, H.-J. (1978). Fuzzy programming and linear programming with several objective functions, Fuzzy Sets Syst., 1 (1), 45–55.
Citations:

The list of publications, citing this article may be empty or incomplete. If you can provide relevant data, please, write on the talk page.