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Year 2025, Volume: 54 Issue: 4, 1479 - 1500, 29.08.2025
https://doi.org/10.15672/hujms.1441627

Abstract

References

  • [1] A.Y. Adhami and F. Ahmad, Interactive Pythagorean-hesitant fuzzy computational algorithm for multi-objective transportation problem under uncertainty, Int. J. Manag. Sci. Eng. Manag. 15 (4), 288297, 2020.
  • [2] M. Akbari, S. Molla-Alizadeh-Zavardehi, and S. Niroomand, Meta-heuristic approaches for fixed-charge solid transportation problem in two-stage supply chain network, Oper. Res. 20 (1), 447471, 2020.
  • [3] B. Amaliah, C. Fatichah, and E. Suryani, A supply selection method for better feasible solution of balanced transportation problem, Expert Syst. Appl. p. 117399, 2022.
  • [4] G. Appa, The transportation problem and its variants, J. Oper. Res. Soc. 24 (1), 7999, 1973.
  • [5] M. Bagheri, A. Ebrahimnejad, S. Razavyan, F. Hosseinzadeh Lotfi, and N. Malekmohammadi, Solving the fully fuzzy multi-objective transportation problem based on the common set of weights in DEA, J. Intell. Fuzzy Syst. 39 (3), 30993124, 2020.
  • [6] M. Bagheri, A. Ebrahimnejad, S. Razavyan, F. Hosseinzadeh Lotfi, and N. Malekmohammadi, Fuzzy arithmetic DEA approach for fuzzy multi-objective transportation problem, Oper. Res. 131, 2022.
  • [7] S.K. Bharati, An interval-valued intuitionistic hesitant fuzzy methodology and application, New Gener. Comput. 39, 377407, 2021.
  • [8] M.B. Bouraima, E. Ayyildiz, G. Ozcelik, N.A. Tengecha, and Z. Stevic, Alternative prioritization for mitigating urban transportation challenges using a Fermatean fuzzybased intelligent decision support model, Neural Comput. Appl. 115, 2024.
  • [9] D. Chakraborty, D.K. Jana, and T.K. Roy, A new approach to solve fully fuzzy transportation problem using triangular fuzzy number, Int. J. Oper. Res. 26 (2), 153179, 2016.
  • [10] A. Charnes and W.W. Cooper, The stepping stone method of explaining linear programming calculations in transportation problems, Manag. Sci. 1 (1), 4969, 1954.
  • [11] D. Chhibber, D.C. Bisht, and P.K. Srivastava, Pareto-optimal solution for fixed-charge solid transportation problem under intuitionistic fuzzy environment, Appl. Soft Comput. 107, 107368, 2021.
  • [12] A. Das, U.K. Bera, and M. Maiti, A solid transportation problem in uncertain environment involving type-2 fuzzy variable, Neural Comput. Appl. 31, 49034927, 2019.
  • [13] S. Dhanasekar, S. Hariharan, and P. Sekar, Fuzzy Hungarian MODI algorithm to solve fully fuzzy transportation problems, Int. J. Fuzzy Syst. 19 (5), 14791491, 2017.
  • [14] A. Ebrahimnejad, An improved approach for solving fuzzy transportation problem with triangular fuzzy numbers, J. Intell. Fuzzy Syst. 29 (2), 963974, 2015.
  • [15] A. Ebrahimnejad and S. Nasseri, Using complementary slackness property to solve linear programming with fuzzy parameters, Fuzzy Inf. Eng. 1 (3), 233245, 2009.
  • [16] H. Garg and R. M. Rizk-Allah, A novel approach for solving rough multi-objective transportation problem: development and prospects, Comput. Appl. Math. 40 (129), 124, 2021.
  • [17] S. Ghosh, S. K. Roy, A. Ebrahimnejad and J. L. Verdegay, Multi-objective fully intuitionistic fuzzy fixed-charge solid transportation problem, Complex Intell. Syst. 7 (2), 10091023, 2021.
  • [18] G. Gupta, Shivani and D. Rani, Neutrosophic goal programming approach for multi-objective fixed-charge transportation problem with neutrosophic parameters, OPSEARCH, 127, 2024.
  • [19] K. Haley, New methods in mathematical programming: the solid transportation problem, Oper. Res. 10 (4), 448463, 1962.
  • [20] F. L. Hitchcock, The distribution of a product from several sources to numerous localities, J. Phys. Math. 20, 224230, 1941.
  • [21] H. Hussein, M. A. Shiker and M. S. Zabiba, A new revised efficient VAM to find the initial solution for the transportation problem, Journal of Physics: Conference Series 1591, 012032, 2020.
  • [22] Y. Kacher and P. Singh, Fuzzy harmonic mean technique for solving fully fuzzy multiobjective transportation problem, J. Comput. Sci. 63, 101782, 2022.
  • [23] K. Karagul and Y. Sahin, A novel approximation method to obtain an initial basic feasible solution of the transportation problem, J. King Saud Univ. 32 (3), 211218, 2020.
  • [24] A. Kaur, J. Kacprzyk and A. Kumar, New methods for solving fully fuzzy solid transportation problems with LR fuzzy parameters, Fuzzy Transportation and Transshipment Problems, Springer, pp. 145184, 2020.
  • [25] H. G. Kocken and M. Sivri, A simple parametric method to generate all optimal solutions of the fuzzy solid transportation problem, Appl. Math. Model. 40, 46124624, 2016.
  • [26] A. Kumar and A. Kaur, Methods for solving unbalanced fuzzy transportation problems, Oper. Res. 12 (3), 287316, 2012.
  • [27] A. Mahmoodirad, T. Allahviranloo and S. Niroomand, A new effective solution method for fully intuitionistic fuzzy transportation problem, Soft Comput. 23 (12), 45214530, 2019.
  • [28] S. Midya, S. K. Roy and V. F. Yu, Intuitionistic fuzzy multi-stage multi-objective fixedcharge solid transportation problem in a green supply chain, Int. J. Mach. Learn. Cyb. 12 (3), 699717, 2021.
  • [29] A. Mondal, S. K. Roy and S. Midya, Intuitionistic fuzzy sustainable multi-objective multi-item multi-choice step fixed-charge solid transportation problem, J. Ambient Intell. Humaniz. Comput. 14 (6), 69756999, 2023.
  • [30] S. Muthuperumal, P. Titus and M. Venkatachalapathy, An algorithmic approach to solving unbalanced triangular fuzzy transportation problems, Soft Comput.24 (24), 1868918698, 2020.
  • [31] D. Rani and T. Gulati, Uncertain multi-objective multi-product solid transportation problems, Sadhana 41 (5), 531539, 2016.
  • [32] S. K. Roy and S. Midya, Multi-objective fixed-charge solid transportation problem with product blending under intuitionistic fuzzy environment, Appl. Intell. 49 (10), 35243538, 2019.
  • [33] S. K. Roy, S. Midya and G.W. Weber, Multi-objective multi-item fixed-charge solid transportation problem under twofold uncertainty, Neural Comput. Appl. 31, 85938613, 2019.
  • [34] S. Sadeghi-Moghaddam, M. Hajiaghaei-Keshteli and M. Mahmoodjanloo, New approaches in metaheuristics to solve the fixed charge transportation problem in a fuzzy environment, Neural Comput. Appl. 31 (1), 477497, 2019.
  • [35] L. Sahoo, Transportation problem in Fermatean fuzzy environment, RAIRO Oper. Res. 57 (1), 145156, 2023.
  • [36] S. Samanta, B. Das and S. K. Mondal, A new method for solving a fuzzy solid transportation model with fuzzy ranking, Asian J. Math. Phy. 2, 7383, 2018.
  • [37] S. Samanta, D. K. Jana, G. Panigrahi and M. Maiti, Novel multi-objective, multi-item and four-dimensional transportation problem with vehicle speed in LR-type intuitionistic fuzzy environment, Neural Comput. Appl. 32, 1193711955, 2020.
  • [38] S. Samanta, A. Ojha, B. Das and S. Mondal, A profit maximisation solid transportation problem using genetic algorithm in fuzzy environment, Fuzzy Inf. Eng. 13 (1), 4057, 2021.
  • [39] Shivani and D. Rani, Solving non-linear fixed-charge transportation problems using nature inspired non-linear particle swarm optimization algorithm, Appl. Soft Comput. 146, 110699, 2023.
  • [40] A. Singh, R. Arora and S. Arora, Bilevel transportation problem in neutrosophic environment, Comput. Appl. Math. 41 (44), 125, 2022.
  • [41] G. Singh and A. Singh, A hybrid algorithm using particle swarm optimization for solving transportation problem, Neural Comput. Appl. 32 (15), 1169911716, 2020.
  • [42] S. Singh and S. Singh, A method for solving bi-objective transportation problem under fuzzy environment, Meta-heuristic Optimization Techniques: Applications in Engineering 10, 37, 2022.
  • [43] R. Srinivasan, N. Karthikeyan, K. Renganathan and D. Vijayan, Method for solving fully fuzzy transportation problem to transform the materials, Mater. Today: Proc. 37 (2), 431433, 2020.
  • [44] L. Zadeh, Fuzzy sets, Information and Control 8 (3), 338353, 1965.
  • [45] H. Zhang, Q. Huang, L. Ma and Z. Zhang, Sparrow search algorithm with adaptive t distribution for multi-objective low-carbon multimodal transportation planning problem with fuzzy demand and fuzzy time, Expert Syst. Appl. 238, 122042, 2024.

Unbalanced fully fuzzy solid transportation problem: Solution strategy and some novel prospects

Year 2025, Volume: 54 Issue: 4, 1479 - 1500, 29.08.2025
https://doi.org/10.15672/hujms.1441627

Abstract

This study investigates the unbalanced solid transportation problem in a fuzzy environment by looking at the importance of solid transportation problem over classical transportation where the supply of sources and the capacity of vehicles are less than the demand for destinations. The solution of such problems obtained by the existing methods involves a dummy source/dummy vehicle or both, but in reality the dummy source or dummy vehicle has no physical significance and the quantity transported either by the dummy source or by the dummy vehicle is not actually transported. In these situations, the demand for some of the destinations remains unfulfilled and the problem is still unsolved in terms of real-life applications. So, the main question is to find the availability of which of the existing sources and the capacity of which vehicle should be increased to fulfill the total destination requirements with the minimum transportation cost possible. To our knowledge, no existing method in the literature could provide us this information. Therefore, a new method has been proposed to fill this gap. By analyzing the optimal solution obtained through the proposed method, we can identify the availability of which sources and the capacity of which vehicles should be increased to fully satisfy demand. Due to the uncertainty occurring in evaluating the parameters of the real-life problem, the data have been considered as triangular fuzzy numbers, and a fuzzy optimal solution is obtained for the same. Finally, a real-life unbalanced solid transport problem is solved to demonstrate the applicability of the suggested methodology.

Ethical Statement

Conflict of interest The authors declare that they have no competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Thanks

The first author is thankful to the Ministry of Human Resource Development, India, for providing financial support, to carry out this work.

References

  • [1] A.Y. Adhami and F. Ahmad, Interactive Pythagorean-hesitant fuzzy computational algorithm for multi-objective transportation problem under uncertainty, Int. J. Manag. Sci. Eng. Manag. 15 (4), 288297, 2020.
  • [2] M. Akbari, S. Molla-Alizadeh-Zavardehi, and S. Niroomand, Meta-heuristic approaches for fixed-charge solid transportation problem in two-stage supply chain network, Oper. Res. 20 (1), 447471, 2020.
  • [3] B. Amaliah, C. Fatichah, and E. Suryani, A supply selection method for better feasible solution of balanced transportation problem, Expert Syst. Appl. p. 117399, 2022.
  • [4] G. Appa, The transportation problem and its variants, J. Oper. Res. Soc. 24 (1), 7999, 1973.
  • [5] M. Bagheri, A. Ebrahimnejad, S. Razavyan, F. Hosseinzadeh Lotfi, and N. Malekmohammadi, Solving the fully fuzzy multi-objective transportation problem based on the common set of weights in DEA, J. Intell. Fuzzy Syst. 39 (3), 30993124, 2020.
  • [6] M. Bagheri, A. Ebrahimnejad, S. Razavyan, F. Hosseinzadeh Lotfi, and N. Malekmohammadi, Fuzzy arithmetic DEA approach for fuzzy multi-objective transportation problem, Oper. Res. 131, 2022.
  • [7] S.K. Bharati, An interval-valued intuitionistic hesitant fuzzy methodology and application, New Gener. Comput. 39, 377407, 2021.
  • [8] M.B. Bouraima, E. Ayyildiz, G. Ozcelik, N.A. Tengecha, and Z. Stevic, Alternative prioritization for mitigating urban transportation challenges using a Fermatean fuzzybased intelligent decision support model, Neural Comput. Appl. 115, 2024.
  • [9] D. Chakraborty, D.K. Jana, and T.K. Roy, A new approach to solve fully fuzzy transportation problem using triangular fuzzy number, Int. J. Oper. Res. 26 (2), 153179, 2016.
  • [10] A. Charnes and W.W. Cooper, The stepping stone method of explaining linear programming calculations in transportation problems, Manag. Sci. 1 (1), 4969, 1954.
  • [11] D. Chhibber, D.C. Bisht, and P.K. Srivastava, Pareto-optimal solution for fixed-charge solid transportation problem under intuitionistic fuzzy environment, Appl. Soft Comput. 107, 107368, 2021.
  • [12] A. Das, U.K. Bera, and M. Maiti, A solid transportation problem in uncertain environment involving type-2 fuzzy variable, Neural Comput. Appl. 31, 49034927, 2019.
  • [13] S. Dhanasekar, S. Hariharan, and P. Sekar, Fuzzy Hungarian MODI algorithm to solve fully fuzzy transportation problems, Int. J. Fuzzy Syst. 19 (5), 14791491, 2017.
  • [14] A. Ebrahimnejad, An improved approach for solving fuzzy transportation problem with triangular fuzzy numbers, J. Intell. Fuzzy Syst. 29 (2), 963974, 2015.
  • [15] A. Ebrahimnejad and S. Nasseri, Using complementary slackness property to solve linear programming with fuzzy parameters, Fuzzy Inf. Eng. 1 (3), 233245, 2009.
  • [16] H. Garg and R. M. Rizk-Allah, A novel approach for solving rough multi-objective transportation problem: development and prospects, Comput. Appl. Math. 40 (129), 124, 2021.
  • [17] S. Ghosh, S. K. Roy, A. Ebrahimnejad and J. L. Verdegay, Multi-objective fully intuitionistic fuzzy fixed-charge solid transportation problem, Complex Intell. Syst. 7 (2), 10091023, 2021.
  • [18] G. Gupta, Shivani and D. Rani, Neutrosophic goal programming approach for multi-objective fixed-charge transportation problem with neutrosophic parameters, OPSEARCH, 127, 2024.
  • [19] K. Haley, New methods in mathematical programming: the solid transportation problem, Oper. Res. 10 (4), 448463, 1962.
  • [20] F. L. Hitchcock, The distribution of a product from several sources to numerous localities, J. Phys. Math. 20, 224230, 1941.
  • [21] H. Hussein, M. A. Shiker and M. S. Zabiba, A new revised efficient VAM to find the initial solution for the transportation problem, Journal of Physics: Conference Series 1591, 012032, 2020.
  • [22] Y. Kacher and P. Singh, Fuzzy harmonic mean technique for solving fully fuzzy multiobjective transportation problem, J. Comput. Sci. 63, 101782, 2022.
  • [23] K. Karagul and Y. Sahin, A novel approximation method to obtain an initial basic feasible solution of the transportation problem, J. King Saud Univ. 32 (3), 211218, 2020.
  • [24] A. Kaur, J. Kacprzyk and A. Kumar, New methods for solving fully fuzzy solid transportation problems with LR fuzzy parameters, Fuzzy Transportation and Transshipment Problems, Springer, pp. 145184, 2020.
  • [25] H. G. Kocken and M. Sivri, A simple parametric method to generate all optimal solutions of the fuzzy solid transportation problem, Appl. Math. Model. 40, 46124624, 2016.
  • [26] A. Kumar and A. Kaur, Methods for solving unbalanced fuzzy transportation problems, Oper. Res. 12 (3), 287316, 2012.
  • [27] A. Mahmoodirad, T. Allahviranloo and S. Niroomand, A new effective solution method for fully intuitionistic fuzzy transportation problem, Soft Comput. 23 (12), 45214530, 2019.
  • [28] S. Midya, S. K. Roy and V. F. Yu, Intuitionistic fuzzy multi-stage multi-objective fixedcharge solid transportation problem in a green supply chain, Int. J. Mach. Learn. Cyb. 12 (3), 699717, 2021.
  • [29] A. Mondal, S. K. Roy and S. Midya, Intuitionistic fuzzy sustainable multi-objective multi-item multi-choice step fixed-charge solid transportation problem, J. Ambient Intell. Humaniz. Comput. 14 (6), 69756999, 2023.
  • [30] S. Muthuperumal, P. Titus and M. Venkatachalapathy, An algorithmic approach to solving unbalanced triangular fuzzy transportation problems, Soft Comput.24 (24), 1868918698, 2020.
  • [31] D. Rani and T. Gulati, Uncertain multi-objective multi-product solid transportation problems, Sadhana 41 (5), 531539, 2016.
  • [32] S. K. Roy and S. Midya, Multi-objective fixed-charge solid transportation problem with product blending under intuitionistic fuzzy environment, Appl. Intell. 49 (10), 35243538, 2019.
  • [33] S. K. Roy, S. Midya and G.W. Weber, Multi-objective multi-item fixed-charge solid transportation problem under twofold uncertainty, Neural Comput. Appl. 31, 85938613, 2019.
  • [34] S. Sadeghi-Moghaddam, M. Hajiaghaei-Keshteli and M. Mahmoodjanloo, New approaches in metaheuristics to solve the fixed charge transportation problem in a fuzzy environment, Neural Comput. Appl. 31 (1), 477497, 2019.
  • [35] L. Sahoo, Transportation problem in Fermatean fuzzy environment, RAIRO Oper. Res. 57 (1), 145156, 2023.
  • [36] S. Samanta, B. Das and S. K. Mondal, A new method for solving a fuzzy solid transportation model with fuzzy ranking, Asian J. Math. Phy. 2, 7383, 2018.
  • [37] S. Samanta, D. K. Jana, G. Panigrahi and M. Maiti, Novel multi-objective, multi-item and four-dimensional transportation problem with vehicle speed in LR-type intuitionistic fuzzy environment, Neural Comput. Appl. 32, 1193711955, 2020.
  • [38] S. Samanta, A. Ojha, B. Das and S. Mondal, A profit maximisation solid transportation problem using genetic algorithm in fuzzy environment, Fuzzy Inf. Eng. 13 (1), 4057, 2021.
  • [39] Shivani and D. Rani, Solving non-linear fixed-charge transportation problems using nature inspired non-linear particle swarm optimization algorithm, Appl. Soft Comput. 146, 110699, 2023.
  • [40] A. Singh, R. Arora and S. Arora, Bilevel transportation problem in neutrosophic environment, Comput. Appl. Math. 41 (44), 125, 2022.
  • [41] G. Singh and A. Singh, A hybrid algorithm using particle swarm optimization for solving transportation problem, Neural Comput. Appl. 32 (15), 1169911716, 2020.
  • [42] S. Singh and S. Singh, A method for solving bi-objective transportation problem under fuzzy environment, Meta-heuristic Optimization Techniques: Applications in Engineering 10, 37, 2022.
  • [43] R. Srinivasan, N. Karthikeyan, K. Renganathan and D. Vijayan, Method for solving fully fuzzy transportation problem to transform the materials, Mater. Today: Proc. 37 (2), 431433, 2020.
  • [44] L. Zadeh, Fuzzy sets, Information and Control 8 (3), 338353, 1965.
  • [45] H. Zhang, Q. Huang, L. Ma and Z. Zhang, Sparrow search algorithm with adaptive t distribution for multi-objective low-carbon multimodal transportation planning problem with fuzzy demand and fuzzy time, Expert Syst. Appl. 238, 122042, 2024.
There are 45 citations in total.

Details

Primary Language English
Subjects Quantitative Decision Methods
Journal Section Statistics
Authors

Shivani - 0000-0003-0770-8899

Deepika Rani 0000-0001-8544-4628

Ali Ebrahimnejad 0000-0001-6003-6601

Early Pub Date June 16, 2025
Publication Date August 29, 2025
Submission Date January 20, 2025
Acceptance Date June 1, 2025
Published in Issue Year 2025 Volume: 54 Issue: 4

Cite

APA -, S., Rani, D., & Ebrahimnejad, A. (2025). Unbalanced fully fuzzy solid transportation problem: Solution strategy and some novel prospects. Hacettepe Journal of Mathematics and Statistics, 54(4), 1479-1500. https://doi.org/10.15672/hujms.1441627
AMA - S, Rani D, Ebrahimnejad A. Unbalanced fully fuzzy solid transportation problem: Solution strategy and some novel prospects. Hacettepe Journal of Mathematics and Statistics. August 2025;54(4):1479-1500. doi:10.15672/hujms.1441627
Chicago -, Shivani, Deepika Rani, and Ali Ebrahimnejad. “Unbalanced Fully Fuzzy Solid Transportation Problem: Solution Strategy and Some Novel Prospects”. Hacettepe Journal of Mathematics and Statistics 54, no. 4 (August 2025): 1479-1500. https://doi.org/10.15672/hujms.1441627.
EndNote - S, Rani D, Ebrahimnejad A (August 1, 2025) Unbalanced fully fuzzy solid transportation problem: Solution strategy and some novel prospects. Hacettepe Journal of Mathematics and Statistics 54 4 1479–1500.
IEEE S. -, D. Rani, and A. Ebrahimnejad, “Unbalanced fully fuzzy solid transportation problem: Solution strategy and some novel prospects”, Hacettepe Journal of Mathematics and Statistics, vol. 54, no. 4, pp. 1479–1500, 2025, doi: 10.15672/hujms.1441627.
ISNAD -, Shivani et al. “Unbalanced Fully Fuzzy Solid Transportation Problem: Solution Strategy and Some Novel Prospects”. Hacettepe Journal of Mathematics and Statistics 54/4 (August2025), 1479-1500. https://doi.org/10.15672/hujms.1441627.
JAMA - S, Rani D, Ebrahimnejad A. Unbalanced fully fuzzy solid transportation problem: Solution strategy and some novel prospects. Hacettepe Journal of Mathematics and Statistics. 2025;54:1479–1500.
MLA -, Shivani et al. “Unbalanced Fully Fuzzy Solid Transportation Problem: Solution Strategy and Some Novel Prospects”. Hacettepe Journal of Mathematics and Statistics, vol. 54, no. 4, 2025, pp. 1479-00, doi:10.15672/hujms.1441627.
Vancouver - S, Rani D, Ebrahimnejad A. Unbalanced fully fuzzy solid transportation problem: Solution strategy and some novel prospects. Hacettepe Journal of Mathematics and Statistics. 2025;54(4):1479-500.