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New approach for solving intuitionistic fuzzy multi-objective transportation problem

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Abstract

Multi-objective transportation problem (MOTP) under intuitionistic fuzzy (IF) environment is analysed in this paper. Due to the fluctuation of market scenario, we assume that the transportation cost, the supply and the demand parameters are not always precise. Hence, the parameters are imprecise, i.e., they are IF numbers. Considering the specific cut interval, the IF transportation cost matrix is converted to interval cost matrix in our proposed problem. Again, using the same concept, the IF supply and the IF demand of the MOTP are reduced to the interval form. Then the proposed MOTP is changed into the deterministic MOTP, which includes interval form of the objective functions. Two approaches, namely intuitionistic fuzzy programming and goal programming, are used to derive the optimal solutions of our proposed problem, and then the optimal solutions are compared. A numerical example is included to illustrate the feasibility and the applicability of the proposed problem. Finally, we present the conclusions with the future scopes of our study.

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References

  1. Zadeh L A 1965 Fuzzy sets. Inf. Control 8: 338–353

    Article  MATH  Google Scholar 

  2. Zimmermann H J 2001 Fuzzy set theory and its applications. Massachusetts: Kluwer

    Book  Google Scholar 

  3. Das S K, Goswami A and Alam S S 1999 Multi-objective transportation problem with interval cost, source and destination parameters. Eur. J. Oper. Res. 117: 100–112

    Article  MATH  Google Scholar 

  4. Li L and Lai K K 2000 A fuzzy approach to the multi-objective transportation problem. Comput. Oper. Res. 27: 43–57

    Article  MathSciNet  MATH  Google Scholar 

  5. Ammar E E and Youness E A 2005 Study on multi-objective transportation problem with fuzzy numbers. Appl. Math. Comput. 166: 241–253

    MathSciNet  MATH  Google Scholar 

  6. Roy S K 2016 Transportation problem with multi-choice cost and demand and stochastic supply. J. Oper. Res. Soc. China 4(2): 193–204

    Article  MathSciNet  MATH  Google Scholar 

  7. Liu S T 2006 Fuzzy total transportation cost measures for solid transportation problem. Appl. Math. Comput. 174: 927–941

    MathSciNet  MATH  Google Scholar 

  8. Roy S K and Mahapatra D R 2011 Multi-objective interval-valued transportation probabilistic problem involving log-normal. Int. J. Math. Sci. Comput. 1(1): 14–21

    MathSciNet  Google Scholar 

  9. Roy S K, Mahapatra D R and Biswal M P 2012 Multi-choice stochastic transportation problem with exponential distribution. J. Uncertain Syst. 6(3): 200–213

    Google Scholar 

  10. Mahapatra D R, Roy S K and Biswal M P 2013 Multi-choice stochastic transportation problem involving extreme value distribution. Appl. Math. Model. 37: 2230–2240

    Article  MathSciNet  MATH  Google Scholar 

  11. Maity G and Roy S K 2014 Solving multi-choice multi-objective transportation problem: a utility function approach. J. Uncertain. Anal. Appl. 2: 1–20

    Article  Google Scholar 

  12. Maity G and Roy S K 2016 Solving a multi-objective transportation problem with nonlinear cost and multi-choice demand. Int. J. Manag. Sci. Eng. Manag. 11(1): 62–70

    Google Scholar 

  13. Rani D and Gulati T R 2016 Uncertain multi-objective multi-product solid transportation problems. Sadhana 41(5): 531–539

    MathSciNet  MATH  Google Scholar 

  14. Maity G, Roy S K and Verdegay J L 2016 Multi-objective transportation problem with cost reliability under uncertain environment. Int. J. Comput. Intell. Syst. 9(5): 839–849

    Article  Google Scholar 

  15. Kocken H G, Ozkok B A and Tiryaki F 2014 A compensatory fuzzy approach to multi-objective linear transportation problem with fuzzy parameters. Eur J. Pure Appl. Math. 7(3): 369–386

    MathSciNet  MATH  Google Scholar 

  16. Roy S K, Maity G, Weber G W and Alparslan Gok S Z 2016 Conic scalarization approach to solve multi-choice multi-objective transportation problem with interval goal. Ann. Oper. Res. 253(1): 599–620 https://doi.org/10.1007/s10479-016-2283-4

    Article  MathSciNet  MATH  Google Scholar 

  17. Rani D, Gulati T R and Kumar A 2014 A method for unbalanced transportation problems in fuzzy environment. Sadhana 39(3): 573–581

    Article  MathSciNet  MATH  Google Scholar 

  18. Roy S K and Maity G 2017 Minimizing cost and time through single objective function in multi-choice interval valued transportation problem. J. Intell. Fuzzy Syst. 32: 1697–1709 https://doi.org/10.3233/JIFS-151656.

    Article  MATH  Google Scholar 

  19. Gupta A and Kumar A 2012 A new method for solving linear multi-objective transportation problems with fuzzy parameters. Appl. Math. Model. 36: 1421–1430

    Article  MathSciNet  MATH  Google Scholar 

  20. Ebrahimnejad A 2016 Fuzzy linear programming approach for solving transportation problems with interval-valued trapezoidal fuzzy numbers. Sadhana 41(3): 299–316

    MathSciNet  MATH  Google Scholar 

  21. Ebrahimnejad A 2016 New method for solving fuzzy transportation problem with LR flat fuzzy numbers. Inf. Sci. 357: 108–124

    Article  Google Scholar 

  22. Roy S K, Maity G and Weber G W 2017 Multi-objective two-stage grey transportation problem using utility function with goals. Cent. Eur. J. Oper. Res. 25: 417–439 https://doi.org/10.1007/s10100-016-0464-5

    Article  MathSciNet  MATH  Google Scholar 

  23. Atanassov K 1986 Intuitionistic fuzzy sets. Fuzzy Sets Syst. 20: 87–96

    Article  MATH  Google Scholar 

  24. Angelov P P 1995 Intuitionistic fuzzy optimization. Notes Intuit. Fuzzy Sets 1(2): 123–129

    Google Scholar 

  25. Jana B and Roy T K 2007 Multi-objective intuitionistic fuzzy linear programming and its application in transportation model. Notes Intuit. Fuzzy Sets 13(1): 34–51

    Google Scholar 

  26. Garg H, Rani M, Sharma S P and Vishwakarma Y 2014 Intuitionistic fuzzy optimization technique for solving multi-objective reliability optimization problems in interval environment. Expert Syst. Appl. 41: 3157–3167

    Article  Google Scholar 

  27. Chakraborty D, Jana D K and Roy T K 2015 A new approach to solve multi-objective multi-choice multi-item Atanaaaov’s intuitionistic fuzzy transportation problem using chance operator. J. Intell. Fuzzy Syst. 28(2): 843–865

    MATH  Google Scholar 

  28. Charnes S and Cooper W W 1961 Management models and industrial application of linear programming. New York: Wiley

    MATH  Google Scholar 

  29. Lee S M 1972 Goal programming for decision analysis. Philadelphia: Auerbach

    Google Scholar 

  30. Ignizio J P 1976 Goal programming and extensions. Lexington: Lexington Books

    Google Scholar 

  31. Aenaida R S and Kwak N W 1994 A linear goal programming for transshipment problems with flexible supply and demand constraints. Fuzzy Sets Syst. 45: 215–224

    Google Scholar 

  32. Abd El-Wahed W F and Lee S M 2006 Interactive fuzzy goal programming for multi-objective transportation problems. Int. J. Manag. Sci. 34: 158–166

    Google Scholar 

  33. Zangiabadi M and Maleki H R 2013 Fuzzy goal programming technique to solve multi-objective transportation problems with some non-linear membership functions. Iran. J. Fuzzy Syst. 10(1): 61–74

    MathSciNet  MATH  Google Scholar 

  34. Kumar P S and Hussain R J 2015 Computationally simple approach for solving fully intuitionistic fuzzy real life transportation problems. Int. J. Syst. Assur. Eng. Manag. 7: 90–101 https://doi.org/10.1007/s13198-014-0334-2.

    Article  Google Scholar 

  35. Mahapatra D R, Roy S K and Biswal M P 2010 Stochastic based on multi-objective transportation problems involving normal randomness. Adv. Model. Optim. 12(2): 205–223

    MathSciNet  MATH  Google Scholar 

  36. De A, Mamanduru V K R, Gunasekaran A, Subramanian N and Tiwari M K 2016 Composite particle algorithm for sustainable integrated dynamic ship routing and scheduling optimization. Comput. Ind. Eng. 96: 201–215

    Article  Google Scholar 

  37. De A, Awasthi A and Tiwari M K 2015 Robust formulation for optimizing sustainable ship routing and scheduling problem. IFAC-PapersOnLine 48(3): 386–373

    Article  Google Scholar 

  38. De A, Kumar S K, Gunasekaran A and Tiwari M K 2016 Sustainable maritime inventory routing problem with time window constraints. Eng. Appl. Artif. Intell. 61: 77–95

    Article  Google Scholar 

  39. Kalayci C B and Kaya C 2016 An ant colony system empowered variable neighborhood search algorithm for the vehicle routing problem with simultaneous pickup and delivery. Expert Syst. Appl. 66: 163–175

    Article  Google Scholar 

  40. Pratap S, Manoj K B, Saxena D and Tiwari M K 2016 Integrated scheduling of rake and stockyard management with ship berthing: a block based evolutionary algorithm. Int. J. Prod. Res. 54(14): 4182–4204

    Article  Google Scholar 

  41. Ray A, De A and Dan P K 2015 Facility location selection using complete and partial ranking MCDM methods. Int. J. Ind. Syst. Eng. 19(2): 262–276

    Google Scholar 

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Acknowledgements

The third author acknowledges the Spanish Ministry of Economy and Competitiveness for partial funding of the Project TIN2014-55024-P and the Andalusian Government for P11-TIC-8001, both from FEDER funds, to this research work. Authors are very much thankful to the Corresponding Editor Professor M K Tiwari and an anonymous reviewer for their constructive comments, which led to improving the quality of the paper.

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Correspondence to SANKAR KUMAR ROY.

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ROY, S.K., EBRAHIMNEJAD, A., VERDEGAY, J.L. et al. New approach for solving intuitionistic fuzzy multi-objective transportation problem. Sādhanā 43, 3 (2018). https://doi.org/10.1007/s12046-017-0777-7

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  • DOI: https://doi.org/10.1007/s12046-017-0777-7

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