International Journal of Analysis and Applications ISSN 2291-8639 (Online)

Research Article

Mastering Complexity: Fuzzy Logic-Driven Optimization for Multi-Objective Transport Solutions Using LINGO Software

  • Zahoor Ahmad Ganie
  • Zahid Gulzar Khaki
  • Tanveer Ahmad Tarray
  • Gazala Salam*
  • Eid Sadun Alotaibi
  • Nahaa Eid Alsubaie

    * Corresponding author

    Abstract

    This work introduces a new method for transportation optimisation decision-making that utilizes LINGO software and fuzzy logic-powered optimisation. The main aim is to minimize variance in accounting for expenses. A sophisticated three-stage stratified random sampling procedure supported by randomised response mechanisms is utilized to achieve this. It primarily contributes a framework through which policymakers can make significant enhancement in the method of collecting data, especially for such cases in which privacy among respondents is very critical. It addresses challenges that face data collection involving sensitive issues and remains within data economy as well as integrity by bringing in fuzzy logic seamlessly in cooperation with randomized response technique.

    How to Cite

    Z. A. Ganie, Z. G. Khaki, T. A. Tarray, G. Salam, E. S. Alotaibi, N. E. Alsubaie, Mastering Complexity: Fuzzy Logic-Driven Optimization for Multi-Objective Transport Solutions Using LINGO Software, Int. J. Anal. Appl. 23 (2025), 222. https://doi.org/10.28924/2291-8639-23-2025-222

    BibTeX
    @article{Ganie2025,
  author  = {Ganie, Zahoor Ahmad and Khaki, Zahid Gulzar and Tarray, Tanveer Ahmad and Salam, Gazala and Alotaibi, Eid Sadun and Alsubaie, Nahaa Eid},
  title   = {Mastering Complexity: Fuzzy Logic-Driven Optimization for Multi-Objective Transport Solutions Using LINGO Software},
  journal = {Int. J. Anal. Appl.},
  volume  = {23},
  year    = {2025},
  pages   = {222},
  doi     = {10.28924/2291-8639-23-2025-222}
}

    References

    • [1] S.L. Warner, Randomized Response: a Survey Technique for Eliminating Evasive Answer Bias, J. Am. Stat. Assoc. 60 (1965), 63–69. https://doi.org/10.2307/2283137.
    • [2] A. Chaudhuri, Randomized Response and Indirect Questioning Techniques in Surveys, Chapman and Hall/CRC, 2016. https://doi.org/10.1201/b10476.
    • [3] J.A. Fox, P.E. Tracy, Randomized Response: A Method for Sensitive Surveys, Sage, 2001.
    • [4] C.R. Gjestvang, S. Singh, A New Randomized Response Model, J. R. Stat. Soc. Ser. B: Stat. Methodol. 68 (2006), 523–530. https://doi.org/10.1111/j.1467-9868.2006.00554.x.
    • [5] M. Guerriero, M.F. Sandri, A Note on the Comparison of Some Randomized Response Procedures, J. Stat. Plan. Inference 137 (2007), 2184–2190. https://doi.org/10.1016/j.jspi.2006.07.004.
    • [6] A.Y.C. KUK, Asking Sensitive Questions Indirectly, Biometrika 77 (1990), 436–438. https://doi.org/10.1093/biomet/77.2.436.
    • [7] T.A. Tarray, H.P. Singh, A Randomized Response Model for Estimating a Rare Sensitive Attribute in Stratified Sampling Using Poisson Distribution, Model Assist. Stat. Appl. 10 (2015), 345–360. https://doi.org/10.3233/mas-150338.
    • [8] L. Zadeh, Fuzzy Sets, Inf. Control. 8 (1965), 338–353. https://doi.org/10.1016/s0019-9958(65)90241-x.
    • [9] H. Malik, A. Iqbal, P. Joshi, S. Agrawal, F.I. Bakhsh, Metaheuristic and Evolutionary Computation: Algorithms and Applications, Springer, (2020).
    • [10] H.P. Singh, T.A. Tarray, Two-stage Stratified Partial Randomized Response Strategies, Commun. Stat. - Theory Methods 52 (2022), 4862–4893. https://doi.org/10.1080/03610926.2013.804571.
    • [11] T.A. Tarray, Z.G. Khaki, Z.A. Ganie, A. Sultan, F. Danish, O. Albalawi, Tri-phase Implementation of an Innovative Fuzzy Logic Approach for Decision-Making, Symmetry 16 (2024), 994. https://doi.org/10.3390/sym16080994.
    • [12] Z.A. Ganie, Z.G. Khaki, T.A. Tarray, G. Salam, E.S. Alotaibi, Optimization of Transportation Efficiency Through Fuzzy Logic and Lingo Software, AIP Adv. 15 (2025), 025227. https://doi.org/10.1063/5.0252654.
    • [13] H.P. Singh, J.M. Kim, T.A. Tarray, A Family of Estimators of Population Variance in Two-Occasion Rotation Patterns, Commun. Stat. - Theory Methods 45 (2016), 4106–4116. https://doi.org/10.1080/03610926.2014.915047.
    • [14] T.A. Tarray, H.P. Singh, A Randomization Device for Estimating a Rare Sensitive Attribute in Stratified Sampling Using Poisson Distribution, Afr. Mat. 29 (2018), 407–423. https://doi.org/10.1007/s13370-018-0550-z.