Skip to main content
Log in

Developing solution algorithm for LR-type fully interval-valued intuitionistic fuzzy linear programming problems using lexicographic-ranking method

  • Published:
Computational and Applied Mathematics Aims and scope Submit manuscript

Abstract

The current article is devoted to mathematically handling the inherent uncertainties of various practical problems by introducing the concept of LR-type interval-valued intuitionistic fuzzy numbers (LR-type IVIFN). The theoretic development of this concept has also been enhanced by providing various diagrammatic representations of LR-type IVIFNs and establishing the arithmetic operations among these fuzzy numbers. The notion of \(\alpha ,\beta \)-cuts and interval arithmetic have been employed to derive the expressions for the arithmetic operations on LR-type IVIFNs. In addition to this, the total order properties of lexicographic-ranking criteria along with considering seven distinct parameters have been used to define the ordering on LR-type IVIFNs. Further, a linear programming problem (LPP) with both equality and inequality type constraints, all parameters in the form of LR-type IVIFNs, and unrestricted decision variables has been modeled. In order to obtain a unique optimal solution for the proposed LPP, the lexicographic ranking-based solution methodology has been developed in which by introducing some binary variables, the original LPP is converted to an equivalent mixed 0-1 lexicographic non-linear programming problem having seven components in the objective function. Various theorems have also been proved to show the equivalence of the original problem and its different proposed constructions. The model formulation, algorithm, and discussed results have not only developed a new idea but also generalized various well-known related works existing in the literature. Moreover, a numerical illustration has been provided to clarify the step-wise procedure of the proposed solution approach. Additionally, to establish the practical significance of the study, a real-world production planning problem is framed, solved, and analyzed under the LR-type interval-valued intuitionistic fuzzy scenario. In last, a comparative study has also been carried out to prove the relevancy of the developed algorithm.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  • Akbari MG, Hesamian G (2018) Signed-distance measures oriented to rank interval-valued fuzzy numbers. IEEE Trans Fuzzy Syst 26:3506–3513

    Google Scholar 

  • Akram M, Allahviranloo T, Pedrycz W, Ali M (2021a) Methods for solving \(LR\)-bipolar fuzzy linear systems. Soft Comput 25:85–108

  • Akram M, Ullah I, Alharbi MG (2021b) Methods for solving \(LR\)-type Pythagorean fuzzy linear programming problems with mixed constraints. Math Probl Eng 2021:1–29

  • Akram M, Ullah I, Allahviranloo T, Edalatpanah S (2021c) Fully Pythagorean fuzzy linear programming problems with equality constraints. Comput Appl Math 40:1–30

  • Akram M, Ullah I, Allahviranloo T, Edalatpanah SA (2021d) \(LR\)-type fully Pythagorean fuzzy linear programming problems with equality constraints. J Intell Fuzzy Syst 41:1975–1992

  • Akram M, Ullah I, Allahviranloo T (2022a) A new method for the solution of fully fuzzy linear programming models. Comput Appl Math 41(1):55

  • Akram M, Ullah I, Allahviranloo T (2022b) A new method to solve linear programming problems in the environment of picture fuzzy sets. Iran J Fuzzy Syst 19:29–49

  • Allahviranloo T, Lotfi FH, Kiasary MK, Kiani N, Alizadeh L (2008) Solving fully fuzzy linear programming problem by the ranking function. Appl Math Sci 2:19–32

    MathSciNet  MATH  Google Scholar 

  • Angelov PP (1997) Optimization in an intuitionistic fuzzy environment. Fuzzy Sets Syst 86:299–306

    MathSciNet  MATH  Google Scholar 

  • Arana-Jiménez M (2018) Nondominated solutions in a fully fuzzy linear programming problem. Math Methods Appl Sci 41:7421–7430

    MathSciNet  MATH  Google Scholar 

  • Arefi M, Taheri SM (2014) Least-squares regression based on Atanassov’s intuitionistic fuzzy inputs-outputs and Atanassov’s intuitionistic fuzzy parameters. IEEE Trans Fuzzy Syst 23:1142–1154

    Google Scholar 

  • Atanassov KT (1986) Intuitionistic fuzzy sets. Fuzzy Sets Syst 20:87–96

    MATH  Google Scholar 

  • Atanassov KT (1999) Intuitionistic fuzzy sets: theory and applications. Studies in fuzziness and soft computing. Physica-Verlag, Heidelberg

  • Atanassov K, Gargov G (1989) Interval valued intuitionistic fuzzy sets. Fuzzy Sets Syst 31:343–349

    MathSciNet  MATH  Google Scholar 

  • Aydın T, Enginoğlu S (2022) Interval-valued intuitionistic fuzzy parameterized interval-valued intuitionistic fuzzy soft matrices and their application to performance-based value assignment to noise-removal filters. Comput Appl Math 41:192

    MathSciNet  MATH  Google Scholar 

  • Bharati SK, Singh S (2018) Transportation problem under interval-valued intuitionistic fuzzy environment. Int J Fuzzy Syst 20:1511–1522

    Google Scholar 

  • Bharati SK, Singh S (2019) Solution of multiobjective linear programming problems in interval-valued intuitionistic fuzzy environment. Soft Comput 23:77–84

    MATH  Google Scholar 

  • Bharati SK, Singh S (2020) Interval-valued intuitionistic fuzzy linear programming problem. New Math Nat Comput 16:53–71

    MATH  Google Scholar 

  • Chen SM, Lee LW (2010) Fuzzy multiple attributes group decision-making based on the ranking values and the arithmetic operations of interval type-2 fuzzy sets. Expert Syst Appl 37:824–833

    Google Scholar 

  • Chen SM, Wang CY (2013) Fuzzy decision making systems based on interval type-2 fuzzy sets. Inf Sci 242:1–21

    MathSciNet  MATH  Google Scholar 

  • Chen SM, Yang MW, Lee LW, Yang SW (2012) Fuzzy multiple attributes group decision-making based on ranking interval type-2 fuzzy sets. Expert Syst Appl 39:5295–5308

    Google Scholar 

  • Das S (2021) Optimization of fuzzy linear fractional programming problem with fuzzy numbers. Big Data Comput Vis 1(1):30–35

    Google Scholar 

  • Das SK, Mandal T, Edalatpanah S (2017) A mathematical model for solving fully fuzzy linear programming problem with trapezoidal fuzzy numbers. Appl Intell 46:509–519

    Google Scholar 

  • Ebrahimnejad A, Verdegay JL (2018) Fuzzy sets-based methods and techniques for modern analytics. Studies in fuzziness and soft computing, vol 364, 1st edn. Springer, Cham. https://doi.org/10.1007/978-3-319-73903-8

  • Enginoǧlu S, Arslan B (2020) Intuitionistic fuzzy parameterized intuitionistic fuzzy soft matrices and their application in decision-making. Comput Appl Math 39:325

    MathSciNet  MATH  Google Scholar 

  • Ezzati R, Khorram E, Enayati R (2015) A new algorithm to solve fully fuzzy linear programming problems using the MOLP problem. Appl Math Model 39:3183–3193

    MathSciNet  MATH  Google Scholar 

  • Farhadinia B (2009) Ranking fuzzy numbers based on lexicographical ordering. Int J Appl Math Comput Sci 5:248–251

    Google Scholar 

  • Garg H, Rani M, Sharma S, Vishwakarma Y (2014) Intuitionistic fuzzy optimization technique for solving multi-objective reliability optimization problems in interval environment. Expert Syst Appl 41:3157–3167

    Google Scholar 

  • Giri PK, Maiti MK, Maiti M (2015) Fully fuzzy fixed charge multi-item solid transportation problem. Appl Soft Comput 27:77–91

    Google Scholar 

  • Gong Z, Zhao W (2018) A novel approach for solving fully fuzzy linear programming problem with LR flat fuzzy numbers. J Comput Anal Appl 24:11–22

    MathSciNet  Google Scholar 

  • Greco S, Figueira J, Ehrgott M (2016) Multiple criteria decision analysis. International series in operations research and management science, vol 233. Springer, New York. https://doi.org/10.1007/978-1-4939-3094-4

  • Hashemi SM, Modarres M, Nasrabadi E, Nasrabadi MM (2006) Fully fuzzified linear programming, solution and duality. J Intell Fuzzy Syst 17:253–261

    MATH  Google Scholar 

  • Hesamian G (2016) Measuring similarity and ordering based on interval type-2 fuzzy numbers. IEEE Trans Fuzzy Syst 25:788–798

    Google Scholar 

  • Hesamian G, Akbari MG (2022) A fuzzy empirical quantile-based regression model based on triangular fuzzy numbers. Comput Appl Math 41:267

    MathSciNet  MATH  Google Scholar 

  • Hosseinzadeh A, Edalatpanah S (2016) A new approach for solving fully fuzzy linear programming by using the lexicography method. Adv Fuzzy Syst

  • Hosseinzadeh E, Tayyebi J (2023) A compromise solution for the neutrosophic multi-objective linear programming problem and its application in transportation problem. J Appl Res Ind Eng 10(1):1–10

    Google Scholar 

  • Ishibuchi H, Tanaka H (1990) Multiobjective programming in optimization of the interval objective function. Eur J Oper Res 48:219–225

    MATH  Google Scholar 

  • Jafar MN, Saeed M, Khan KM, Alamri FS, Khalifa HAEW (2022) Distance and similarity measures using max-min operators of neutrosophic hypersoft sets with application in site selection for solid waste management systems. IEEE Access 10:11220–11235

    Google Scholar 

  • Kane L, Bado H, Diakite M, Konate M, Kane S, Traore K (2021) Solving semi-fully fuzzy linear programming problems. Int J Res Ind Eng 10(3):251–275

    MATH  Google Scholar 

  • Kaur J, Kumar A (2012) Unique fuzzy optimal value of fully fuzzy linear programming problems. Control Cybern 41:497–508

    MathSciNet  MATH  Google Scholar 

  • Kaur J, Kumar A (2013) Mehar’s method for solving fully fuzzy linear programming problems with LR fuzzy parameters. Appl Math Model 37:7142–7153

    MathSciNet  MATH  Google Scholar 

  • Kaur J, Kumar A (2016) Unique fuzzy optimal value of fully fuzzy linear programming problems with equality constraints having \(LR\) flat fuzzy numbers. In: An introduction to fuzzy linear programming problems: theory, methods and applications, vol 340. Springer, Cham, pp 109–118

  • Khan IU, Ahmad T, Maan N (2013) A simplified novel technique for solving fully fuzzy linear programming problems. J Optim Theory Appl 159:536–546

    MathSciNet  MATH  Google Scholar 

  • Kumar A, Kaur J (2014) Fuzzy optimal solution of fully fuzzy linear programming problems using ranking function. J Intell Fuzzy Syst 26:337–344

    MathSciNet  MATH  Google Scholar 

  • Kumar PS, Hussain RJ (2016) Computationally simple approach for solving fully intuitionistic fuzzy real life transportation problems. Int J Syst Assur Eng Manag 7:90–101

    Google Scholar 

  • Kumar A, Kaur J, Singh P (2011) A new method for solving fully fuzzy linear programming problems. Appl Math Model 35:817–823

    MathSciNet  MATH  Google Scholar 

  • Lotfi FH, Allahviranloo T, Jondabeh MA, Alizadeh L (2009) Solving a full fuzzy linear programming using lexicography method and fuzzy approximate solution. Appl Math Model 33:3151–3156

    MathSciNet  MATH  Google Scholar 

  • Mahapatra G, Roy T (2009) Reliability evaluation using triangular intuitionistic fuzzy numbers arithmetic operations. World Acad Sci Eng Technol 50:574–581

    Google Scholar 

  • Mahmoodirad A, Allahviranloo T, Niroomand S (2019) A new effective solution method for fully intuitionistic fuzzy transportation problem. Soft Comput 23:4521–4530

    MATH  Google Scholar 

  • Mahmoudi F, Nasseri SH (2019) A new approach to solve fully fuzzy linear programming problem. J Appl Res Ind Eng 6(2):139–149

    Google Scholar 

  • Mekawy I (2022) A novel method for solving multi-objective linear fractional programming problem under uncertainty. J Fuzzy Ext Appl 3(2):169–176

    Google Scholar 

  • Mottaghi A, Ezzati R, Khorram E (2015) A new method for solving fuzzy linear programming problems based on the fuzzy linear complementary problem (FLCP). Int J Fuzzy Syst 17:236–245

    MathSciNet  Google Scholar 

  • Nagoorgani A, Ponnalagu K (2012) A new approach on solving intuitionistic fuzzy linear programming problem. Appl Math Sci 6:3467–3474

    MathSciNet  MATH  Google Scholar 

  • Najafi HS, Edalatpanah S (2013) A note on “a new method for solving fully fuzzy linear programming problems’’. Appl Math Model 37:7865–7867

    MathSciNet  MATH  Google Scholar 

  • Najafi HS, Edalatpanah S, Dutta H (2016) A nonlinear model for fully fuzzy linear programming with fully unrestricted variables and parameters. Alex Eng J 55:2589–2595

    Google Scholar 

  • Niroomand S (2018) A multi-objective based direct solution approach for linear programming with intuitionistic fuzzy parameters. J Intell Fuzzy Syst 35:1923–1934

    MathSciNet  Google Scholar 

  • Ozkok BA, Albayrak I, Kocken HG, Ahlatcioglu M (2016) An approach for finding fuzzy optimal and approximate fuzzy optimal solution of fully fuzzy linear programming problems with mixed constraints. J Intell Fuzzy Syst 31:623–632

    MATH  Google Scholar 

  • Pérez-Cañedo B, Concepción-Morales ER (2019a) A method to find the unique optimal fuzzy value of fully fuzzy linear programming problems with inequality constraints having unrestricted \(LR\) fuzzy parameters and decision variables. Expert Syst Appl 123:256–269

  • Pérez-Cañedo B, Concepción-Morales ER (2019b) On \(LR\)-type fully intuitionistic fuzzy linear programming with inequality constraints: solutions with unique optimal values. Expert Syst Appl 128:246–255

  • Rahmani A, Hosseinzadeh Lotfi F, Rostamy-Malkhalifeh M, Allahviranloo T (2016) A new method for defuzzification and ranking of fuzzy numbers based on the statistical beta distribution. Adv Fuzzy Syst

  • Ranjbar M, Effati S, Miri SM (2022) Fully hesitant fuzzy linear programming with hesitant fuzzy numbers. Eng Appl Artif Intell 114:105047

    Google Scholar 

  • Rezaei A, Oner T, Katican T, Smarandache F, Gandotra N (2022) A short history of fuzzy, intuitionistic fuzzy, neutrosophic and plithogenic sets. Int J Neutrosophic Sci 18(1): 99–116

  • Roy SK, Ebrahimnejad A, Verdegay JL, Das S (2018) New approach for solving intuitionistic fuzzy multi-objective transportation problem. Sādhanā 43:1–12

    MathSciNet  MATH  Google Scholar 

  • Saghi S, Nazemi A, Effati S, Ranjbar M (2023) Simplex algorithm for hesitant fuzzy linear programming problem with hesitant cost coefficient. Iran J Fuzzy Syst 20:137–152

    MathSciNet  Google Scholar 

  • Şahin R (2016) Fuzzy multicriteria decision making method based on the improved accuracy function for interval-valued intuitionistic fuzzy sets. Soft Comput 20:2557–2563

    MATH  Google Scholar 

  • Sidhu SK, Kumar A (2019) Mehar methods to solve intuitionistic fuzzy linear programming problems with trapezoidal intuitionistic fuzzy numbers. In: Deep K, Jain M, Salhi S (eds) Performance prediction and analytics of fuzzy, reliability and queuing models. Asset Analytics. Springer Berlin, pp 265–282

  • Singh SK, Yadav SP (2015) Modeling and optimization of multi objective non-linear programming problem in intuitionistic fuzzy environment. Appl Math Model 39:4617–4629

    MathSciNet  MATH  Google Scholar 

  • Singh V, Yadav SP (2017) Development and optimization of unrestricted LR-type intuitionistic fuzzy mathematical programming problems. Expert Syst Appl 80:147–161

    Google Scholar 

  • Suresh M, Vengataasalam S, Prakash KA (2014) Solving intuitionistic fuzzy linear programming problems by ranking function. J Intell Fuzzy Syst 27:3081–3087

    MathSciNet  MATH  Google Scholar 

  • Tadesse A, Acharya M, Sahoo M, Acharya S (2021) Fuzzy linear programming problem with fuzzy decision variables: a geometrical approach. J Stat Manag Syst 24:853–863

    Google Scholar 

  • Tamilarasi G, Paulraj S (2022) An improved solution for the neutrosophic linear programming problems based on Mellin’s transform. Soft Comput 26(17):8497–8507

    Google Scholar 

  • Tanaka H, Asai K (1984) Fuzzy solution in fuzzy linear programming problems. IEEE Trans Syst Man Cybern 2:325–328

    MATH  Google Scholar 

  • Voskoglou M (2020) Assessment and linear programming under fuzzy conditions. https://doi.org/10.22105/jfea.2020.253436.1024

  • Wan SP, Wang F, Lin LL, Dong JY (2015) An intuitionistic fuzzy linear programming method for logistics outsourcing provider selection. Knowl Based Syst 82:80–94

    Google Scholar 

  • Wang P, Lin Y, Fu M, Wang Z (2023) VIKOR method for plithogenic probabilistic linguistic MAGDM and application to sustainable supply chain financial risk evaluation. Int J Fuzzy Syst 25:780–793

    Google Scholar 

  • Yang X, Lin TY, Yang J, Li Y, Yu D (2009) Combination of interval-valued fuzzy set and soft set. Comput Math Appl 58:521–527

    MathSciNet  MATH  Google Scholar 

  • Zadeh LA (1965) Information and control. Fuzzy Sets 8:338–353

    Google Scholar 

  • Zhang SF, Liu SY, Zhai RH (2011) An extended GRA method for MCDM with interval-valued triangular fuzzy assessments and unknown weights. Comput Ind Eng 61:1336–1341

    Google Scholar 

  • Zhao J, Li B, Rahman AU, Saeed M (2023) An intelligent multiple-criteria decision-making approach based on sv-neutrosophic hypersoft set with possibility degree setting for investment selection. Manag Decis 61:472–485

    Google Scholar 

  • Zimmermann HJ (1975) Description and optimization of fuzzy systems. Int J Gen Syst 2:209–215

    MATH  Google Scholar 

  • Zulqarnain RM, Siddique I, Ali R, Jarad F, Iampan A (2023) Aggregation operators for interval-valued Pythagorean fuzzy hypersoft set with their application to solve MCDM problem. CMES Comput Model Eng Sci 135(1):619–651

Download references

Acknowledgements

The authors would like to sincerely thank the Editor-in-Chief and anonymous referees for their insightful comments and recommendations which have significantly enhanced both the quality and clarity of the paper. The first author is also grateful to the Ministry of Human Resource Development, India, for financial support, to carry out this research work.

Funding

No funding was received to assist with the preparation of this manuscript.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to S. K. Gupta.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Additional information

Communicated by Graçaliz Pereira Dimuro.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Malik, M., Gupta, S.K. & Arana-Jiménez, M. Developing solution algorithm for LR-type fully interval-valued intuitionistic fuzzy linear programming problems using lexicographic-ranking method. Comp. Appl. Math. 42, 274 (2023). https://doi.org/10.1007/s40314-023-02408-5

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s40314-023-02408-5

Keywords

Mathematics Subject Classification

Navigation