Literature Review of Fuzzy Set Theory: Applications and Methodologies
DOI:
https://doi.org/10.33095/9p0kjy98Keywords:
Fuzzy Sets; Fuzzy linear programming; Fuzzy linear regression; Fuzzy Analytic Hierarchy Process.Abstract
This paper represents a comprehensive literature survey of the research published in the Journal of Economics and Administrative Sciences (JEAS) on applications and methodologies of fuzzy set theory. The review traced how fuzzy logic has been evolving in decision-making, optimization, and modeling uncertainties in published articles such as economics, management, and engineering. The categorization of fuzzy methodologies into various domains such as fuzzy linear programming, fuzzy regression, fuzzy control systems, and fuzzy multi-criteria decision-making relies heavily on the study of existing research. An analysis revealed an increasing trend of investigations highlighting the interplay of fuzzy logic with artificial intelligence, statistical modeling, and heuristic optimization methods. The developments in methodologies of fuzzy decision-making frameworks are again examined from the perspective of applicability in real-life problem situations involving imprecise and uncertain data. Findings that fuzzy logic, therefore, contributed considerably to the enhancement of problem-solving in economics and administrative sciences through more flexible and adaptive models. Therefore, this literature review will be an excellent guide for researchers in fuzzy set theory applications to grasp existing gaps and suggest future directions for improving fuzzy methodologies across industries.
Downloads
References
Abd Al-Razzaq, S. S., & Mohammed, J. M. (2022). Estimation of Causal Effect of treatment via Fuzzy Regression Discontinuity Designs. Journal of Economics and Administrative Sciences, 28(134), 110–117. https://doi.org/10.33095/jeas.v28i134.2424
Abdulqader Mansoor, S., & Yarub Maan, H. (2024). Evaluating and Prioritizing the Sustainable Supply Chain Management Practices in Food Industry. Journal of Economics and Administrative Sciences, 30(141), 264–280. https://doi.org/10.33095/zwgmg912
Albadri, F. F., & Ali, Y. A. (2019). Use multi-goal fuzzy programming to find the critical path. Journal of Economics and Administrative Sciences, 25(112), 428–443. https://doi.org/10.33095/jeas.v25i112.1672
Al-doori, E. A., & Laith Fadhil S. H. (2016). Fuzzy logic in the estimate of reliability function for k - components systems. Journal of Economics and Administrative Sciences, 22(87), 391. https://doi.org/10.33095/jeas.v22i87.717
Al-Douri, M. S., & Hamdi, I. M. (2018). Using Mehar method to change fuzzy cost of fuzzy linear model with practical application. Journal of Economics and Administrative Sciences, 24(104), 314. https://doi.org/10.33095/jeas.v24i104.87
Al-Kazaz, Q. N., & Al-Saadi, H. J. K. (2017). Comparing Bayes estimation with Maximum Likelihood Estimation of Generalized Inverted Exponential Distribution in Case of Fuzzy Data. Journal of Economics and Administrative Sciences, 23(101). https://doi.org/10.33095/jeas.v23i101.199
Al-Maadidi, M. W. A., & Alsammak, M. A. J. (2016). Adoption of Membership Level for Critical Activities In Knowledge Chain Model Building An Investigation Analytical Study Depending on Fuzzy Logic Architecture for Organizations Pushed by Knowledge. Journal of Economics and Administrative Sciences, 22(93), 242. https://doi.org/10.33095/jeas.v22i93.433
Aseel Sameer Mohamed. (2015). Constructing fuzzy linear programming model with practical application. Journal of Economics and Administrative Sciences, 21(83), 328. https://doi.org/10.33095/jeas.v21i83.656
Ashour, M. A. H. (2009). Fuzzy Linear Programming problems. Journal of Economics and Administrative Sciences, 15(56), 181. https://doi.org/10.33095/jeas.v15i56.1271
Ashour, M. A. H., & Jawad, M. A. (2017). Using Fuzzy Games Theory to Determine the optimal Strategy for The Mobile Phone Networks in The Baghdad and Basra governorates. Journal of Economics and Administrative Sciences, 23(95), 399. https://doi.org/10.33095/jeas.v23i95.394
Ayed, B. S., & Khalaf, S. W. (2022). Planning the Production of the Electrical Distribution Converter (400KV/11) Using Time Series Methods and Goal Programming in the Fuzzy Environment. In Journal of Economics and Administrative Sciences (Vol. 28, Issue 131). https://doi.org/10.33095/jeas.v28i131.2231
Ayed, S. B., & Khalaf, W. S. (2021). Using Fuzzy Inference to Evaluation Suppliers in Diyala General Electric Industries Company. Journal of Economics and Administrative Sciences, 27(130), 1–24. https://doi.org/10.33095/jeas.v27i130.2188
Baha Alwan, E., & Abdulmohsin Ali, O. (2024). About Semi-parametric Methodology for Fuzzy Quantile Regression Model Estimation: A Review. Journal of Economics and Administrative Sciences, 29(138), 127–146. https://doi.org/10.33095/jeas.v29i138.3044
Bakhayt, A.-G. K., & Fayyad, A. H. (2015). Use of model sales man fuzzy multi-objective linear for speed up and rationing in the transport mechanism used in the General Company for grain Processing. Journal of Economics and Administrative Sciences, 21(81), 299. https://doi.org/10.33095/jeas.v21i81.579
Bakhayt, A.-G. K., & Kamel, R. D. (2017). Fuzzy aggregate production planning by using fuzzy Goal programming with practical application. Journal of Economics and Administrative Sciences, 23(99), 355. https://doi.org/10.33095/jeas.v23i99.260
Battikh, A. H. (2014). Solve travelling sales man problem by using fuzzy multi-objective linear programming. Journal of Economics and Administrative Sciences, 20(75), 432. https://doi.org/10.33095/jeas.v20i75.599
Bellman, R. E., & Zadeh, L. A. (1970). Decision-Making in a Fuzzy Environment. Management Science, 17(4), B-141-B-164. https://doi.org/10.1287/mnsc.17.4.B141
Hasan, H. A., & Mohammed, M. J. (2024). Classification of Iraqi Children According to Their Nutritional Status Using Fuzzy Logic. Journal of Economics and Administrative Sciences, 29(138), 161–171. https://doi.org/10.33095/jeas.v29i138.3046
Ibrahim, S. K., & Hadi, A. A. (2024). Solve the fuzzy Assignment problem by using the Labeling method. Journal of Economics and Administrative Sciences, 24(106), 446. https://doi.org/10.33095/jeas.v24i106.34
Ibrahim Tawfeeq*, A., & Hazim Aboudi, E. (2024). Some Fuzzy Least Squares Estimators for Regression Model Using Different Kernel Functions. Journal of Economics and Administrative Sciences, 30(142), 465–375. https://doi.org/10.33095/7qdnc433
Jassim Nassir, M., & Yousef Abdul Redha, N. (2024). An Integrated Approach to Constraints Theory and Fuzzy Analytical Hierarchy Process (FAHP) in Construction Projects (Case Study). Journal of Economics and Administrative Sciences, 30(143), 68–85. https://doi.org/10.33095/4bgyes38
Jawad, L. B., & Hassan, Z. F. (2018). Adoption of multi – model Assignment Fuzzy to find Optimizing for the use of internet line in the Ministry of Science and Technlogy . Journal of Economics and Administrative Sciences, 21(84), 357. https://doi.org/10.33095/jeas.v21i84.708
Jeter, A. S. (2018). Fuzzy Multi-Objective Capacitated Transportation Problem with Mixed Constraints using different forms of membership functions. Journal of Economics and Administrative Sciences, 24(107), 614. https://doi.org/10.33095/jeas.v24i107.1315
Kareem, R. E., & Mohammed, M. J. (2023). Fuzzy Bridge Regression Model Estimating via Simulation. Journal of Economics and Administrative Sciences, 29(136), 60–69. https://doi.org/10.33095/jeas.v29i136.2607
Khalaf, W. S. , & Mohammed, A. H. (2013). Solution of Fuzzy Maximal Flow Problems of Vehicles in Province of Diwaniyah Using the Ranking Function for Fuzzy Linear Programming Model. Journal of Economics And Administrative Sciences, 19(73)., 430-450., 19(73), 430–450.
Khalaf, W. S., & Abd Ahmed, M. (2016). Material Requirements Planning for the Electric Motor in Fuzzy Environment for State Company for Electric Industries. Journal of Economics and Administrative Sciences, 22(90), 170. https://doi.org/10.33095/jeas.v22i90.504
Khalaf, W. S., & Halim, H. D. (2018). Find the fuzzy maximum flow of Imam Kadhimen visitors using fuzzy dynamic programming University of Baghdad - Faculty of Administration and Economics. Journal of Economics and Administrative Sciences, 24(103), 102. https://doi.org/10.33095/jeas.v24i103.106
Khalaf, W. S., & Jassim, A. B. (2017). Inventory control by using Fuzzy set theory An Applied Research at the Baghdad Soft Drinks Company. Journal of Economics and Administrative Sciences, 23(101), 72. https://doi.org/10.33095/jeas.v23i101.170
Mihnatan, R. S., & Khalaf, W. S. (2019). The Time-Cost Trade-off to Manage A Project in a Fuzzy Environment. Journal of Economics and Administrative Sciences, 25(114), 498–522. https://doi.org/10.33095/jeas.v25i114.1748
Mohammed, A. H., & Ashour, M. A. H. (2024). Constructing a Hybrid Algorithm to Model the Physical and Chemical Inspection Station Data of the Shatt Al-Arab Waters*. Journal of Economics and Administrative Sciences, 30(141), 457–478. https://doi.org/10.33095/qe4m1z69
Mohammed, M. J. (2020). Fuzzy Robust Estimation For Location Parameter. Journal of Economics and Administrative Sciences, 26(117), 480–491. https://doi.org/10.33095/jeas.v26i117.1825
Mohammed, M. J., & Abbas, A. F. (2018). A Comparision Between Membership function And Entropy Function In Fuzzy Adaptive Linear Regression. Journal of Economics and Administrative Sciences, 24(103), 453. https://doi.org/10.33095/jeas.v24i103.123
Mohammed, Z. M. (2013). Comparison between Process Control Charts and Fuzzy Multinomial Control Charts with Practical Appliance. Journal of Economics and Administrative Sciences, 19(73), 471. https://doi.org/10.33095/jeas.v19i73.1076
N. Basheer, Y., & Y. Maan, H. (2020). Fuzzy Analytic Hierarchy Process FEAHP to Prioritize The Evaluation of The Main and Subsidiary Criteria in B2B Industrial Market Sectors – Applied Research. Journal of Economics and Administrative Sciences, 26(124), 460–480. https://doi.org/10.33095/jeas.v26i124.2052
Nori Al-Hakeem, A. A. H., & Dawood, F. S. (2021). Evaluation suppliers according to the integration of the Quality Function Deployment and the Fuzzy Analytic Hierarchy Process. Journal of Economics and Administrative Sciences, 27(125), 170–192. https://doi.org/10.33095/jeas.v27i125.2071
Qusay Alshebly *, O., & Najm Abdullah, S. (2024). The Fuzziness Models with The Proposed New Conjugate Gradient Method for The Classification of High-Dimensional Data in Bioinformatics. Journal of Economics and Administrative Sciences, 30(142), 425–448. https://doi.org/10.33095/ahnw8r72
Redha, S. M., & Hassan, N. A. K. (2014). Employment programming fuzzy goal in medical field. Journal of Economics and Administrative Sciences, 20(76), 363. https://doi.org/10.33095/jeas.v20i76.682
Saffawi, S. Y., & warttan, H. A. (2018). Comparative study of between P chart and Multinomial Fuzzy quality control chart ( FM). Journal of Economics and Administrative Sciences, 24(104), 329. https://doi.org/10.33095/jeas.v24i104.88
Saleh, S. A. (2016). New Approach for Solving Symmetric Fuzzy Linear Programming Problem. Journal of Economics and Administrative Sciences, 22(91), 1. https://doi.org/10.33095/jeas.v22i91.495
Shemail, A. H., & Mohammed, M. J. (2022). Semi Parametric Logistic Regression Model with the Outputs Representing Trapezoidal Intuitionistic Fuzzy Number. Journal of Economics and Administrative Sciences, 28(133), 70–81. https://doi.org/10.33095/jeas.v28i133.2350
Tanaka†, H., Okuda, T., & Asai, K. (1973). On Fuzzy-Mathematical Programming. Journal of Cybernetics, 3(4), 37–46. https://doi.org/10.1080/01969727308545912
Yawiz, Z. (2015). Reliability Estimation Of Fuzzy Failure Times Of Free Distribution And It Use To Estimate The Fuzzy Reliability Of Mosul Dam. Journal of Economics and Administrative Sciences, 21(81), 348. https://doi.org/10.33095/jeas.v21i81.583
Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338–353. https://doi.org/10.1016/S0019-9958(65)90241-X
Zimmermann, H.-J. (1978). Fuzzy programming and linear programming with several objective functions. Fuzzy Sets and Systems, 1(1), 45–55. https://doi.org/10.1016/0165-0114(78)90031-3
Published
Issue
Section
License
Copyright (c) 2025 Journal of Economics and Administrative Sciences
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Articles submitted to the journal should not have been published before in their current or substantially similar form or be under consideration for publication with another journal. Please see JEAS originality guidelines for details. Use this in conjunction with the points below about references, before submission i.e. always attribute clearly using either indented text or quote marks as well as making use of the preferred Harvard style of formatting. Authors submitting articles for publication warrant that the work is not an infringement of any existing copyright and will indemnify the publisher against any breach of such warranty. For ease of dissemination and to ensure proper policing of use, papers and contributions become the legal copyright of the publisher unless otherwise agreed.
The editor may make use of Turnitin software for checking the originality of submissions received.
