Abstract
Intuitionistic fuzzy set theory is a generalized version of classical fuzzy set theory, where membership degree of acceptance and membership degree of rejection are both measured. In the present study, we formulate a balanced transportation problem with multiple objectives having all parameters and variables as intuitionistic fuzzy numbers. The problem is first reduced to a crisp multiobjective transportation problem using accuracy function on each objective function and then an algorithm is proposed to solve the problem. In the solution procedure, linear, exponential and hyperbolic membership functions are used to tackle intuitionistic fuzzy constraints related with each objective. To show the relations among the intuitionistic fuzzy transportation problem, its equivalent crisp formulation and the problems obtained by applying different membership functions, various theorems are established. Finally, two numerical examples are illustrated to clarify the steps involved in the proposed algorithm and to draw the comparison among linear, exponential and hyperbolic membership functions.
Similar content being viewed by others
Change history
30 August 2019
This erratum is published because vendor overlooked corrections related to Theorems 3 to 5.
References
Abd El-Wahed, W. F., & Lee, S. M. (2006). Interactive fuzzy goal programming for multi-objective transportation problems. International Journal of Management Sciences, 34, 158–166.
Ammar, E. E., & Youness, E. A. (2005). Study on multi-objective transportation problem with fuzzy numbers. Applied Mathematics and Computation, 166, 241–253.
Angelov, P. P. (1997). Optimization in an intuitionistic fuzzy environment. Fuzzy Sets and Systems, 86, 299–306.
Atanassov, K. T. (1986). Intuitionistic fuzzy sets. Fuzzy Sets and Systems, 20, 87–96.
Bharti, S. K., & Singh, S. R. (2019). Solution of multiobjective linear programming problems in interval valued intuitionistic fuzzy environment. Soft Computing, 23, 77–84.
Bit, A. K., Biswal, M. P., & Alam, S. S. (1992). Fuzzy programming approach to multicriteria decision making transportation problem. Fuzzy Sets and Systems, 50, 135–141.
Chakraborty, D., Jana, D. K., & Roy, T. K. (2015). A new approach to solve multi-objective multi-choice multi-item Atanassov’s intuitionistic fuzzy transportation problem using chance operator. Journal of Intelligent and Fuzzy Systems, 28, 843–865.
Chanas, S., & Kuchta, D. (1996). A concept of the optimal solution of the transportation problem with fuzzy cost coefficients. Fuzzy Sets and Systems, 82, 299–305.
Charnes, A., & Cooper, W. W. (1954). The stepping stone method for explaining linear programming calculation in transportation problem. Management Science, 1, 49–69.
Dhingra, A. K., & Moskowitz, H. (1991). Application of fuzzy theories to multiple objective decision making in system design. European Journal of Operational Research, 53, 348–361.
Diaz, J. A. (1979). Finding a complete description of all efficient solutions to a multiobjective transportation problem. Ekonomicko-Matematicky Obzor, 15, 62–73.
Ebrahimnejad, A., & Verdegay, J. L. (2018). A new approach for solving fully intuitionistic fuzzy transportation problems. Fuzzy Optimization and Decision Making, 17, 447–474.
Garg, H., Rani, M., Sharma, S. P., & Vishwakarma, Y. (2014). Intuitionistic fuzzy optimization technique for solving multi-objective reliability optimization problems in interval environment. Expert Systems with Applications, 41, 3157–3167.
Gupta, A., & Kumar, A. (2012). A new method for solving linear multi-objective transportation problems with fuzzy parameters. Applied Mathematical Modelling, 36, 1421–1430.
Gupta, P., & Mehlawat, M. K. (2009). Bector-Chandra type duality in fuzzy linear programming with exponential membership function. Fuzzy Sets and Systems, 160, 3290–3308.
Hitchcock, F. L. (1941). The distribution of a product from several sources to numerous locations. Journal of Mathematics and Physics, 20, 224–230.
Jana, B., & Roy, T. K. (2007). Multi-objective intuitionistic fuzzy linear programming and its application in transportation model. Notes on Intuitionistic Fuzzy Sets, 13, 34–51.
Kocken, H. G., Ozlok, B. A., & Tiryaki, F. (2014). A compensatory fuzzy approach to multi-objective transportation problems with fuzzy parameters. European Journal of Pure and Applied Mathematics, 7, 369–386.
Kumar, P. S., & Hussain, R. J. (2016). Computationally simple approach for solving fully intuitionistic fuzzy real life transportation problems. International Journal of System Assurance Engineering and Management, 7, 90–101.
Leberling, H. (1981). On finding compromise solutions for multicriteria problems using the fuzzy min-operator. Fuzzy Sets and Systems, 6, 105–118.
Li, L., & Lai, K. K. (2000). A fuzzy approach to multiobjective transportation problem. Computers and Operations Research, 27, 43–57.
Mahmoodirad, A., Allahviranloo, T., & Niroomand, S. (2018). A new effective solution method for fully intuitionistic fuzzy transportation problem. Soft Computing, 1–10.
Pal, B. B., Moitra, B. N., & Maulik, U. (2003). A goal programming procedure for fuzzy multiobjective linear fractional programming problem. Fuzzy Sets and Systems, 139, 395–405.
Peidro, D., & Vasant, P. (2011). Transportation planning with modified s-curve membership functions using an interactive fuzzy multi-objective approach. Applied Soft Computing, 11, 2656–2663.
Rani, D., Gulati, T. R., & Garg, H. (2016). Multi-objective non-linear programming problem in intuitionistic fuzzy environment: Optimistic and pessimistic view point. Expert Systems with Applications, 64, 228–238.
Rani, D., Gulati, T. R., & Kumar, A. (2014). A method for unbalanced transportation problems in fuzzy environment. Sadhana, 39, 573–581.
Roy, S. K., Ebrahimnejad, A., Verdegay, J. L., & Das, S. (2018). New approach for solving intuitionistic fuzzy multi-objective transportation problem. Sadhana, 43(1), 3.
Sakawa, M. (1993). Fuzzy Sets and Interactive Multiobjective Optimization. New York: Plenum Press.
Singh, S. K., & Yadav, S. P. (2018). Intuitionistic fuzzy multi-objective linear programming problem with various membership functions. Annals of Operations Research, 269, 693–707.
Verma, R., Biswal, M. P., & Biswas, A. (1997). Fuzzy programming technique to solve multi-objective transportation problems with some non-linear membership functions. Fuzzy Sets and Systems, 91, 37–43.
Zadeh, L. A. (1965). Fuzzy sets. Information and Computation, 8, 338–353.
Zangiabadi, M., & Maleki, H. R. (2007). Fuzzy goal programming for multiobjective transportation problems. Journal of Applied Mathematics and Computing, 24, 449–460.
Zangiabadi, M., & Maleki, H. R. (2013). Fuzzy goal programming technique to solve multi-objective transportation problems with some non-linear membership functions. Iranian Journal of Fuzzy Systems, 10, 61–74.
Acknowledgements
The authors sincerely acknowledge the valuable suggestions and recommendations of the anonymous reviewers, which has considerably improved the presentation and quality of the paper. The first author is also thankful to the Quality Improvement Programme cell of IIT Roorkee and Punjab Engineering College, Chandigarh along with All India Council of Technical Education for their support to carry out this work.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Mahajan, S., Gupta, S.K. On fully intuitionistic fuzzy multiobjective transportation problems using different membership functions. Ann Oper Res 296, 211–241 (2021). https://doi.org/10.1007/s10479-019-03318-8
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10479-019-03318-8