[1] Amini, K. and Rashidi, M. On determining radius in nonmonotone trust‐region approaches,
J. Math. Modeling, 11(3) (2023), 507–526.
[2] Ansary, M.A.T. and Panda, G. A sequential quadratic programming method for constrained
multiobjective optimization problems, J. Appl. Math. Comput. 64(1) (2020), 379–397.
[3] Bandyopadhyay, S., Pal, S.K. and Aruna, B. Multiobjective GAs, quantitative indices, and
pattern classification, IEEE Trans. Syst. Man Cybern. B Cybern. 34(5) (2004), 2088–2099.
[4] Bazaraa, M.S. and Goode, J.J. An algorithm for solving linearly constrained minimax
problems, Eur. J. Oper. Res. 11(2) (1982), 158–166.
[5] Burke, J.V., Curtis, F.E. and Wang, H. A sequential quadratic optimization algorithm with
rapid infeasibility detection, SIAM J. Optim. 24(2) (2014), 839–872.
[6] Carrizo, G.A., Fazzio, N.S. and Schuverdt, M.L. A nonmonotone projected gradient method
for multiobjective problems on convex sets, J. Oper. Res. Soc. China, 12(2) (2024), 410–427.
[7] Chen, J. Liu, J. Qin, X. and Yao, J.-C. A nonmonotone proximal gradient algorithm for
solving nonsmooth multiobjective optimization problems with an extending application to
robust multiobjective optimization, J. Comput. Appl. Math. 460 (2025).
[8] Chen, W. Yang, X. and Zhao, Y. Conditional gradient method for vector optimization,
Comput. Optim. Appl. 85(3) (2023), 857–896.
[9] Collette, Y. and Siarry, P. Multiobjective optimization: Principles and case studies,
Springer Science & Business Media, 2003.
[10] Custódio, A.L., Madeira, J.F., Vaz, A.I. and Vicente, L. N. Direct multisearch for multi-
objective optimization, SIAM J. Optim. 21 (2011), 1109–1140.
[11] Dai, Y.-H. On the Nonmonotone Line Search, J. Optim. Theory Appl. 112 (2002), 315–330.
[12] Deb, K. Multiobjective optimization using evolutionary algorithms, John Wiley & Sons,
2001.
[13] Deb, K., Pratap, A. and Meyarivan, T. Constrained test problems for multiobjective evo-
lutionary optimization, in Evolutionary Multi‐Criterion Optimization, Springer, Berlin,
Heidelberg, 2001, 284–298.
[14] Deb, K., Thiele, L., Laumanns, M. and Zitzler, E. Scalable test problems for evolutionary
multiobjective optimization, Springer, London, 2005.
[15] Dolan, E.D. and Moré , J.J. Benchmarking optimization software with performance profiles,
Math. Program. 91 (2002), 201–213.
[16] Dolatnezhadsomarin, A. and Khorram, E. Two efficient algorithms for constructing almost
even approximations of the Pareto front in multiobjective optimization problems, Eng.
Optim. 51(4) (2019), 567–589.
[17] Drummond, L.M.G. A projected gradient method for vector optimization problems, Com-
put. Optim. Appl. 28 (2004), 5–29.
[18] Drummond, L.M.G. and Svaiter, B.F. A steepest descent method for vector optimization,
J. Comput. Appl. Math. 175 (2005), 395–414.
[19] Ehrgott, M. Multicriteria optimization, Springer, Berlin, 2005.
[20] Eichfelder, G. Adaptive scalarization methods in multiobjective optimization, Springer,
Berlin, 2008.
[21] Fliege, J., Drummond, L.M.G. and Svaiter, B.F. Newton’s method for multiobjective op-
timization, SIAM J. Optim. 20(2) (2009), 602–626.
[22] Fliege, J. and Svaiter, B.F. Steepest descent methods for multicriteria optimization, Math.
Methods Oper. Res. 51 (2000), 479–494.
[23] Fliege, J. and Vaz, A.I.F. A method for constrained multiobjective optimization based on
SQP techniques, SIAM J. Optim. 26(4) (2016), 2091–2119.
[24] Gebken, B., Peitz, S. and Dellnitz, M. A descent method for equality and inequality con-
strained multiobjective optimization problems, in Numerical and Evolutionary Optimiza-
tion – NEO 2017, Springer International Publishing, 2018, 29–61.
[25] Ghalavand, N., Khorram, E. and Morovati, V. Two adaptive nonmonotone trust‐region
algorithms for solving multiobjective optimization problems, Optimization, 73(9) (2023),
2953–2985.
[26] Gonçalves, D.S., Gonçalves, M.L.N. and Melo, J.G. An away‐step Frank–Wolfe algorithm
for constrained multiobjective optimization, Comput. Optim. Appl. 88(3) (2024), 759–781.
[27] Grippo, L., Lampariello, F. and Lucidi, S. A nonmonotone line search technique for New-
ton’s method, SIAM J. Numer. Anal. 23 (1986), 707–716.
[28] Hwang, C.-L. and Masud, A.S.M. Multiple objective decision making—Methods and appli-
cations, Lecture Notes in Economics and Mathematical Systems, vol. 164, Springer, Berlin,
1979.
[29] Knowles, J. Thiele, L. and Zitzler, E. A Tutorial on the Performance Assessment of Stochas-
tic Multiobjective Optimizers, TIK Report 214, Computer Engineering and Networks Lab-
oratory, ETH Zurich, 2006.
[30] Mahdavi‐Amiri, N. and Salehi Sadaghiani, F. A superlinearly convergent nonmono-
tone quasi‐Newton method for unconstrained multiobjective optimization, Optim. Methods
Softw. 35(6) (2020), 1223–1247.
[31] Mangasarian, O.L. and Fromovitz, S. The Fritz John necessary optimality conditions in the
presence of equality and inequality constraints, J. Math. Anal. Appl. 17(1) (1967), 37–47.
[32] Miettinen, K. Nonlinear multiobjective optimization, International Series in Operations
Research and Management Science, vol. 12, Springer Science and Business Media, 2012.
[33] Morovati, V. and Pourkarimi, L. Extension of Zoutendijk method for solving constrained
multiobjective optimization problems, Eur. J. Oper. Res. 273(1) (2019), 44–57.
[34] Pinheiro, M.E. and Grapiglia, G.N. Universal nonmonotone line search method for noncon-
vex multiobjective optimization problems with convex constraints, Comput. Appl. Math.
44(1) (2025), 56.
[35] Pirouz, B. and Khorram, E. A computational approach based on the ε-constraint method
in multiobjective optimization problems, Adv. Appl. Stat. 49(6) (2016), 453–483.
[36] Rashidi, M., Khorram, E. and Soleimani-Damaneh, M. An exact penalty method with
nonmonotone line search and rapid infeasibility detection for constrained multiobjective
optimization: Application in supervised machine learning, Comput. Oper. Res. 188 (2026),
107351.
[37] Rashidi, M. and Soleimani‐damaneh, M. MultiSQP-GS: a sequential quadratic program-
ming algorithm via gradient sampling for nonsmooth constrained multiobjective optimiza-
tion, Comput. Optim. Appl. 89 (2024), 729–767.
[38] Tanabe, H., Fukuda, E.H., and Yamashita, N. An accelerated proximal gradient method
for multiobjective optimization, Comput. Optim. Appl. 86(2) (2023), 421–455.
[39] Upadhayay, A., Ghosh, D., Jauny, Yao, J.C. and Zhao, X. A nonmonotone conditional
gradient method for multiobjective optimization problems, Soft Comput. 28(17-18) (2024),
9609–9630.
[40] Upadhayay, A., Ghosh, D. and Kumar, K. Nonmonotone Wolfe‐type quasi‐Newton methods
for multiobjective optimization problems, Optimization, (2025), 1–33.
[41] Zhang, H.C. and Hager, W.W. A nonmonotone line search technique for unconstrained
optimization, SIAM J. Optim. 14(4) (2004), 1043–1056.
[42] Zhao, X., Raushan, R., Ghosh, D., Yao, J.-C. and Qi, M. Proximal gradient method
for convex multiobjective optimization problems without Lipschitz continuous gradients,
Comput. Optim. Appl. 91(1) (2025), 27–66.
[43] Zhao, X. and Yao, J.-C. Linear convergence of a nonmonotone projected gradient method
for multiobjective optimization, J. Global Optim. 82(3) (2022), 577–594.
[44] Zitzler, E., Thiele, L., Laumanns, M., Fonseca, C.M. and da Fonseca, V.G. Performance as-
sessment of multiobjective optimizers: an analysis and review, IEEE Trans. Evol. Comput.
7(2) (2003), 117–132.
