Recent Advances and Future Directions in Fuzzy Optimization (2020–2025)

1. Zhai, M., Fang, Y., Yang, J., Chen, H., Xu, J., & Zhang, Y. (2022). A review on history, trends and perspectives of fuzzy
linear programming models and methods. Expert Systems with Applications, 194, Article 116524.
https://doi.org/10.1016/j.eswa.2022.116524
2. Karimi, N., Gandomi, A. H., & Tavakoli, H. R. (2022). Fuzzy multi-objective programming: A systematic literature review and taxonomy
(2020–2022). Expert Systems with Applications, 206, Article 117865. https://doi.org/10.1016/j.eswa.2022.117865
3. Gu, X., Li, Y., & Wang, Z. (2023). Autonomous learning for fuzzy systems: A review of structure and parameter learning. Artificial
Intelligence Review, 56(8), 8593–8646. https://doi.org/10.1007/s10462-023-10427-x
4. Xie, Y., Zhang, Q., & Li, H. (2024). Two-stage evolutionary algorithm with fuzzy preference indicator for many-objective optimization.
Swarm and Evolutionary Computation, 85, Article 101480. https://doi.org/10.1016/j.swevo.2023.101480
5. Castillo, O., Kacprzyk, J., & Bustince, H. (2024). A survey on Type-3 fuzzy logic systems and their applications in control. IEEE/CAA
Journal of Automatica Sinica, 11(8), 1744–1756. https://doi.org/10.1109/JAS.2024.124530
6. Ala, A., Mohseni, F., & Rahmani, R. (2024). A fuzzy multi-objective optimization model for sustainable supply chain design. Applied
Soft Computing, 150, Article 111012. https://doi.org/10.1016/j.asoc.2023.1110127. Kousar, S., Ali, M., & Khan, T. (2025). Fuzzy multi-objective optimization model to design a sustainable closed-loop manufacturing
system. PeerJ Computer Science, 11, Article e2591. https://doi.org/10.7717/peerj-cs.2591
8. Varshney, A. K., & Kumar, S. (2023). Literature review of the recent trends and applications in fuzzy rule-based systems and optimization.
International Journal of Fuzzy Systems, 25(6), 2163–2186. https://doi.org/10.1007/s40815-023-01509-y
9. Mukhtadi, S. A. (2023). Fuzzy multi-objective optimization to evaluate supplier performance taking into account visibility and supply-
chain risk. Foundations of Computing and Decision Sciences, 48(3), 385–397. https://doi.org/10.2478/fcds-2023-0017
10. (MDPI Special Issue Editorial) Riaz, M. (2022). Recent advances in fuzzy optimization methods and models [Editorial]. Symmetry,
14(11), Article 2368. https://doi.org/10.3390/sym14112368
11. (MathSJ) Alka, B., & Kumar, A. (2023). Multi-objective fuzzy linear programming techniques: Methods and applications. Mathematics
Journal, 8(5), 224–229.
12. Alharbi, B., Singh, A. K., & Dwivedi, S. K. (2021). Algorithms, models, and applications of fuzzy optimization: Special issue summary.
CMES - Computer Modeling in Engineering & Sciences, 129(1), 1–3. https://doi.org/10.32604/cmes.2021.17835
13. Kumar, P. S. (2021, September). Solving optimization problems using fuzzy and intuitionistic fuzzy-set approaches: A new algorithmic
approach [Conference presentation]. Proceedings of the International Conference on Fuzzy Systems and Optimization, (Springer, preprint
version).
14. Nozari, H., Nassar, S., & Szmelter-Jarosz, A. (2025). Fuzzy multi-objective optimization model for resilient supply chain financing based
on blockchain and IoT. Digital, 5(3), 32. https://doi.org/10.3390/digital5030032
15. Liu, J., Zhang, L., & Chen, Y. (2023). Convex optimization-based adaptive fuzzy control for a class of uncertain nonlinear systems. IEEE
Transactions on Fuzzy Systems, 31(8), 2650–2659. https://doi.org/10.1109/TFUZZ.2022.3228303
16. Bharathi, D., & Srinivas, P. (2021). Optimizing fuzzy nonlinear programming problems: Methods and comparative study. Journal of
Fuzzy Optimization & Applications, 6(2), 12–23. https://doi.org/10.59569/JFZNLA.2022.6.2.02
17. Mukherjee, A., & Pandey, P. (2021). Fuzzy and probabilistic approaches in water distribution network optimization: A review and
comparative study. Water Science and Technology, 83(11), 2715–2730. https://doi.org/10.2166/wst.2021.144
18. Sutikno, T. (2023). Fuzzy optimization and metaheuristic algorithms. Babylonian Journal of Mathematics, 2023, 59–65.
https://doi.org/10.58496/BJM/2023/012
19. Dhull, A., Singh, A., & Gupta, G. (2022). A survey on fuzzy systems optimization using evolutionary algorithms and swarm intelligence
[Preprint]. ResearchGate.
20. https://www.researchgate.net/publication/359237178_A_Survey_on_Fuzzy_Systems_Optimization_Using_Evolutionary_Algorithms_a
nd_Swarm_Intelligence
21. Rodríguez-Abreo, O., & Santos, L. (2024). Fuzzy logic controller for UAV flight stability with gains optimized via genetic algorithms.
Heliyon, 10(4), Article e26363. https://doi.org/10.1016/j.heliyon.2024.e26363
22. Ahmadini, A. A. H., & Ahmad, F. (2021). Solving intuitionistic fuzzy multi-objective linear programming problems under neutrosophic
uncertainty. AIMS Mathematics, 6(5), 4556–4580. https://doi.org/10.3934/math.2021269
23. Moloodpoor, M., Karimi, R., & Farahmand, H. (2025). A comparative review of fuzzy-reinforced metaheuristic search methods for
engineering optimization. International Journal of Intelligent Systems.
24. Flores-Siguenza, P., Lopez-Sanchez, V., Mosquera-Gutierres, J., Llivisaca-Villazhañay, J., Moscoso-Martínez, M., & Guamán, R. (2025).
Fuzzy optimization and life cycle assessment for sustainable supply chain design: Applications in the dairy industry. Sustainability, 17(12),
Article 5634. https://doi.org/10.3390/su17125634.