Abstract
The main investigation of the paper is to develop the restricted fixed charge solid transportation problem under a hybrid uncertain environment where fuzziness and roughness coexist. A fuzzy rough STP model is developed by integrating the classical STP, fuzzy set theory, and rough set theory, which apparently provide a way to accommodate the uncertainty. For solving the problem, we apply the fuzzy rough expected value operator and propose the possibility based STP model with fuzzy rough parameters on a rough space. A numerical example is presented to describe the fuzzy rough approach using Lingo 13.0 optimization software. Finally, a graphical presentation has also shown to describe the comparison between two proposed approaches. Some important managerial decisions are also drawn by observing the optimal result.
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References
Zadeh, L.A.: Concept of a linguistic variable and its application to approximate reasoning I. Inf. Sci. 8, 199–249 (1975)
Liu, S.T.: Fuzzy total transportation cost measures for fuzzy solid transportation problem. Appl. Math. Comput. 174, 927–941 (2006)
Hitchcock, F.L.: The distribution of a product from several sources to numerous localities. J. Math. Phys. 20, 224–230 (1941)
Das, A., Bera, U.K., Das, B.: A solid transportation problem with mixed constraint in different environment. J. Appl. Anal. Comput. 6(1), 179–195 (2016)
Haley, K.: The solid transportation problem. Oper. Res. 10, 448–463 (1962)
Pawlak, Z., Skowron, A.: Rudiment of rough sets. Inf. Sci. 177, 3–27 (2007)
Kundu, P., Kar, S., Maiti, M.: Some solid transportation models with crisp and rough cost. Int. J. Math. Comput. Sci. Eng. 7(1), 13–20 (2013)
Shiraz, R.K., Charle, V., Jalalzadeh, L.: Fuzzy rough DEA model: a possibility and expected value approaches. Expert Syst. Appl. 41, 434–444 (2014)
Pawlak, Z.: Rough sets. Int. J. Inf. Comput. Sci. 11(5), 341–356 (1982)
Das, A., Bera, U.K., Maiti, M.: A profit maximizing solid transportation model under rough interval approach. IEEE Trans. Fuzzy Syst. 25(3), 485–498 (2016)
Polkowski, L., Skowron, A. (eds.): Rough sets and current trends in computing. Lecture Notes in Artificial Intelligence, vol. 1424. Springer (1998)
Polkowski, L., Skowron, A. (eds.): Rough sets in knowledge discovery, vol. 1–2. Springer (1998)
Polkowski, L., Tsumoto, S., Lin, T.Y. (eds.): Rough set methods and applications–new developments in knowledge discovery in information systems. Springer (2000)
Zhong, N., Skowron, A., Ohsuga, S. (eds.): New direction in rough sets, data mining, and granular-soft computing, vol. 11. Springer (1999)
Das, A., Bera, U.K., Maiti, M.: A breakable multi-item multi stage solid transportation problem under budget with Gaussian type-2 fuzzy parameters. Appl. Intell. 45(3), 923–951 (2016)
Das, A., Bera, U.K., Maiti, M.: Defuzzification of trapezoidal type-2 fuzzy variables and its application to solid transportation problem. J. Intell. Fuzzy Syst. 30(4), 2431–2445 (2016)
Sinha, B., Das, A., Bera, U.K.: Profit maximization solid transportation problem with trapezoidal interval type-2 fuzzy numbers. Int. J. Appl. Comput. Math. 2(1), 41–56 (2016)
Zadeh, L.A.: Fuzzy Sets. Inf. Control 8, 338–353 (1965)
Maity, G., Roy, S.K.: Solving a multi-objective transportation problem with nonlinear cost and multi-choice demand. Int. J. Manag. Sci. Eng. Manag. 11(1), 62–70 (2016)
Maity, G., Roy, S.K., Verdegay, J.L.: Multi-objective transportation problem with cost reliability under uncertain environment. Int. J. Comput. Intell. Syst. 9(5), 839–849 (2016)
Roy, S.K., Maity, G., Weber, G.W.: Multi-objective two-stage grey transportation problem using utility function with goals. Cent. Eur. J. Oper. Res. 25(2), 417–439 (2017)
Roy, S.K., Maity, G., Weber, G.M., Gök, S.Z.: Conic scalarization approach to solve multi-choice multi-objective transportation problem with interval goal. Ann. Oper. Res. 253(1), 599–620 (2017)
Roy, S.K., Maity, G.: Minimizing cost and time through single objective function in multi-choice interval transportation problem. J. Intell. Fuzzy Syst. 32(3), 1697–1709 (2017)
Maity, G., Roy, S.K.: Solving multi-objective transportation problem with interval goal using utility function approach. Int. J. Oper. Res. 27(4), 513–529 (2016)
Sun, Y., Zhang, G., Hong, Z., Dong, K.: How uncertain information on service capacity influences the intermodal routing decision: a fuzzy programming perspective. Information 9(1), 24 (2018)
Zheng, Y., Liu, B.: Fuzzy vehicle routing model with credibility measure and its hybrid intelligent algorithm. Appl. Math. Comput. 176(2), 673–683 (2005)
Mula, J., Peidro, D., Poler, R.: The effectiveness of a fuzzy mathematical programming approach for supply chain production planning with fuzzy demand. Int. J. Prod. Econ. 128(1), 136–143 (2010)
Sun, Y., Hrušovský, M., Zhang, C., Lang, M.: A time-dependent fuzzy programming approach for the green multimodal routing problem with rail service capacity uncertainty and road traffic congestion. Complexity 2018(8645793), 22 (2018)
Kundu, P., Kar, S., Maiti, M.: Multi-objective multi-item solid transportation problem in fuzzy environment. Appl. Math. Model. 37(4), 2028–2038 (2013)
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Sengupta, D., Das, A., Dutta, A., Bera, U.K. (2020). A Fixed Charge Solid Transportation Problem with Possibility and Expected Value Approaches in Hybrid Uncertain Environment. In: Castillo, O., Jana, D., Giri, D., Ahmed, A. (eds) Recent Advances in Intelligent Information Systems and Applied Mathematics. ICITAM 2019. Studies in Computational Intelligence, vol 863. Springer, Cham. https://doi.org/10.1007/978-3-030-34152-7_14
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