Abstract
A new version of fractional minimal cost flow problem with fuzzy arc costs is focused in this study. The fuzzy arc costs are applied as in most of the real-world applications, the parameters have high degree of uncertainty. The goal of this problem is to determine the minimum fuzzy fractional cost of sending and passing a specified flow value into and from a network. A decomposition-based solution methodology is introduced to tackle this problem. The methodology applies Zadeh’s extension principle to decompose the problem to two upper bound and lower bound problems. These problems are capable of being solved for different \(\alpha\)-cut values to construct the fuzzy fractional minimal cost flow value as the objective function value. The efficiency of the proposed solution methodology is studied over some well-known examples of fractional minimal cost flow problem. The obtained results show the superiority of the proposed approach comparing to the methods of the literature.
Similar content being viewed by others
References
Ahuja, R.K., Magnanti, T.L., Orlin, J.B.: Network Flows. Prentice-Hall, Englewood Cliffs (1993)
Badri, H., Fatemi Ghomi, S.M.T., Hejazi, T.H.: A two-stage stochastic programming model for value-based supply chain network design. Sci. Iran. 23(1), 348–360 (2016)
Bazaraa, M.S., Jarvis, J.J., Sherali, H.D.: Linear Programming and Network Flows. Wiley, New York (2010)
Charnes, A., Cooper, W.W.: Programming with linear fractional functionals. Naval Res. Logist. Q. 9(3–4), 181–186 (1962)
Dhanasekar, S., Hariharan, S., Sekar, P.: Fuzzy Hungarian MODI algorithm to solve fully fuzzy transportation problems. Int. J. Fuzzy Syst. (2016). doi:10.1007/s40815-016-0251-4
Ebrahimnejad, A., Nasseri, S.H., Mansourzadeh, S.M.: Modified bounded dual network simplex algorithm for solving minimum cost flow problem with fuzzy costs based on ranking functions. J. Intell. Fuzzy Syst. 24, 191–198 (2013)
Fakhri, A., Ghatee, M.: Fractional multi-commodity flow problem: duality and optimality conditions. Appl. Math. Model. 38, 2151–2162 (2014)
GAMS Software, http://www.gams.com/ (2016)
Ghasemi, R., Nikfar, M., Roghanian, E.: A revision on area ranking and deviation degree methods of ranking fuzzy numbers. Sci. Iran. 22(3), 1142–1154 (2015)
Ghatee, M., Hashemi, S.M., Zarepisheh, M., Khorram, E.: Preemptive priority-based algorithms for fuzzy minimal cost flow problem: an application in hazardous materials transportation. Comput. Ind. Eng. 57, 341–354 (2009)
Ghatee, M., Hashemi, S.M.: Generalized minimal cost flow problem in fuzzy nature: an application in bus network planning problem. Appl. Math. Model. 32, 2490–2508 (2008)
Ghatee, M., Hashemi, S.M.: Application of fuzzy minimum cost flow problems to network design under uncertainty. Fuzzy Sets Syst. 160, 3263–3289 (2009)
Gilmore, P.C., Gomory, R.E.: A linear programming approach to the cutting stock problem—part II. Oper. Res. 11(6), 863–888 (1963)
Kaufmann, A., Gupta, M.M.: Fuzzy Mathematical Models in Engineering and Management Scienc. Elsevier, Amsterdam (1988)
Kaufmann, A., Gupta, M.M.: Introduction to Fuzzy Arithmetics: Theory and Applications. Van Nostrand Reinhold, New York (1991)
Kaufmann, A.: Introduction to the Theory of Fuzzy Subsets, vol. 1. Academic Press, New York (1975)
Khalili, S., Mohammadzade, H., Fallahnezhad, M.S.: A new approach based on queuing theory for solving the assembly line balancing problem using fuzzy prioritization techniques. Sci. Iran. 23(1), 387–398 (2016)
Singh, S.K., Yadav, S.P.: Fuzzy programming approach for solving intuitionistic fuzzy linear fractional programming problem. Int. J. Fuzzy Syst. 18(2), 263–269 (2016)
Liu, S.T., Kao, C.: Solving fuzzy transportation problems based on extension principle. Eur. J. Oper. Res. 153, 661–674 (2004)
Liu, S.T.: Fuzzy total transportation cost measures for fuzzy solid transportation problem. Appl. Math. Comput. 174, 927–941 (2006)
Liu, S.T.: Fuzzy profit measures for a fuzzy economic order quantity model. Appl. Math. Model. 32, 2076–2086 (2008)
Liu, S.T.: Fractional transportation problem with fuzzy parameters. Soft. Comput. 20, 3629–3636 (2016)
Niroomand, S., Mahmoodirad, A., Heydari, A., Kardani, F., Hadi-Vencheh, A.: An extension principle based solution approach for shortest path problem with fuzzy arc lengths. Oper. Res. (2016). doi:10.1007/s12351-016-0230-4
Sherali, H.D.: On a fractional minimal cost flow problem on networks. Optim. Lett. 6, 1945–1949 (2012)
Toksarı, M.D., Bilim, Y.: Interactive fuzzy goal programming based on Jacobian matrix to solve decentralized bi-level multi-objective fractional programming problems. Int. J. Fuzzy Syst. 17(4), 499–508 (2015)
Veeramani, C., Sumathi, M.: Fuzzy mathematical programming approach for solving fuzzy linear fractional programming problem. FUZZ-IEEE (2013). doi:10.1109/FUZZ-IEEE.2013.6622568
Xu, C., Xu, X.M., Wang, H.F.: The fractional minimal cost flow problem on network. Optim. Lett. 5(2), 307–317 (2011)
Yager, R.R.: A characterization of the extension principle. Fuzzy Sets Syst. 18, 205–217 (1986)
Yang, J., Fei, W., Li, D.F.: Non-linear programming approach to solve bi-matrix games with payoffs represented by I-fuzzy numbers. Int. J. Fuzzy Syst. 18(3), 492–503 (2016)
Zadeh, L.A.: Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets Syst. 1, 3–28 (1978)
Zimmermann, H. J.: Fuzzy Set Theory and Its Applications, 3rd edn. Kluwer-Nijhoff, Boston (1996)
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Mahmoodirad, A., Niroomand, S., Mirzaei, N. et al. Fuzzy Fractional Minimal Cost Flow Problem. Int. J. Fuzzy Syst. 20, 174–186 (2018). https://doi.org/10.1007/s40815-017-0293-2
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s40815-017-0293-2