1. F. Akbari, M. Ghaznavi, and E. Khorram, A revised Pascoletti-Serafini scalarization method for multiobjective optimization problems, Journal of Optimization Theory and
Applications, 178(2), 560–590 (2018).
2. S. M. Alirahmi, S. Bashiri Mousavi, A. R. Razmi, and P. A. Ahmadi, A comprehensive techno-economic analysis and multi-criteria optimization of a compressed air energy
storage (CAES) hybridized with solar and desalination units, Energy Conversion and Management, 236, 114193 (2021).
3. S. B. Amor, F. Belaid, R. Benkraiem, B. Ramdani, and K. Guesmi, Multi-criteria classification, sorting, and clustering: A bibliometric review and research agenda, Annals of
Operations Research, 325(1), 1–32 (2023).
4. D. Cheng, Y. Yao, R. Liu, and et al. Precision agriculture management based on a surrogate model assisted multiobjective algorithmic framework, Scientific Reports, 13(1),
1–13 (2023).
5. D. Jing, M. Imeni, S. A. Edalatpanah, A. Alburaikan, H. A. E. W. Khalifa, Optimal selection of stock portfolios using multi-criteria decision-making methods, Mathematics,
11(2), 411 (2023).
6. M. Ehrgott, S. Ruzika, Improved ϵ-constraint method for multiobjective programming, Journal of Optimization Theory and Applications, 138(3), 375–394 (2008).
7. G. Eichfelder, Adaptive scalarization methods in multiobjective optimization. Springer, (2008).
8. A. Engau, M. M. Wiecek, Generating epsilon-efficient solutions in multiobjective programming, European Journal of Operational Research, 177(3), 1566–1579 (2007).
9. Y. Gao, X. Yang, and K. L. Teo, Optimality conditions for approximate solutions in vector optimization problems. Journal of Industrial and Management Optimization,
7(2), 387–396 (2011).
10. B. A. Ghaznavi-ghosoni, E. Khorram, On approximating weakly/properly efficient solutions in multiobjective programming, Mathematical and Computer Modelling, 54(11-
12), 3172–3181 (2011).
11. B. A. Ghaznavi, E. Khorram, and M. Soleimani-Damaneh, Scalarization for characterization of approximate strong/weak/proper efficiency in multiobjective optimization,
Journal of Optimization Theory and Applications, 154(2), 587–600 (2012).
12. A. M. Khalid, H. M. Hamza, S. Mirjalili, and K. M. Hosny, MOCOVIDOA: A novel multiobjective coronavirus disease optimization algorithm for solving multiobjective op-
timization problems, Neural Computing and Applications, 35(16), 13839–13866, (2023).
13. K. Khaledian, E. Khorram, and B. Karimi, Characterizing ε-properly efficient solutions, Optimization Methods and Software, 30(2), 583–593 (2014).
14. S. S. Kutateladze, Convex ε-programming, Soviet Mathematics–Doklady, 20(2), 391–393 (1979).
15. G. Lin, On min-norm and min–max methods of multi-objective optimization. Mathematical Programming, 103(1), 1–33 (2005).
16. J. C. Liu, ε-Properly efficient solution to nondifferentiable multi-objective programming problems, Applied Mathematics Letters, 12(3), 109–113 (1999).
17. P. Loridan, ε-Solutions in vector minimization problems, Journal of Optimization Theory and Applications, 43(2), 265–276 (1984).
18. A. Mahajan, I. Singh, and N. Arora, An integrated multi-criteria decision-making frame-work for the selection of sustainable biodegradable polymer for food packaging applica-
tions, Environmental Development and Sustainability, 26(3), 8399–8420 (2024).
19. R. T. Marler, J. S. Arora, The weighted sum method for multi-objective optimization:New insights, Structural and Multidisciplinary Optimization, 41(6), 853–862 (2010).
20. A. Pascoletti, P. Serafini, Scalarizing vector optimization problems, Journal of Optimization Theory and Applications, 42(4), 499–524 (1984).
21. N. Rastegar, E. Khorram, A combined scalarizing method for multiobjective programming problems, European Journal of Operational Research, 236(1), 229–237 (2014).
22. H. Salmei, M. A. Yaghoobi, Improving the min-max method for multiobjective programming. Operations Research Letters, 48(5), 480–486 (2020).
23. L. Shao, M. Ehrgott, Approximately solving multiobjective linear programs in objective space and an application in radiotherapy treatment planning, Mathematical Methods
of Operations Research, 68(2), 257–276. (2008a).
24. L. Shao, L., M. Ehrgott, Approximating the nondominated set of an MOLP by approximately solving its dual problem, Mathematical Methods of Operations Research, 68(3),
469–492 (2008b).
25. H. Tuy, Convex analysis and global optimization, Springer, (2016).
26. D. J. White, Epsilon-dominating solutions in mean-variance portfolio analysis, European Journal of Operational Research, 105(2), 457–466 (1998).
27. H. Zhao, X. Hao, Location decision of electric vehicle charging station based on a novel grey correlation comprehensive evaluation multi-criteria decision method, Energy, 299,
131356 (2024).
)