References
- Sawaragi Y, Nakayama H, Tanino T. Theory of multiobjective optimization. Orlando, FL: Academic Press; 1985.
- Luc DT. Theory of vector optimization. Berlin: Springer; 1989.
- Chen GY, Huang XX, Yang XQ. Vector optimization: set-valued and variational analysis. Berlin: Springer; 2005.
- Jahn J. Vector optimization-theory, applications, and extensions. Berlin: Springer; 2011.
- Ansari QH, Yao J-C, editors. Recent developments in vector optimization. Berlin: Springer; 2012.
- Chinchuluun A, Pardalos PM. A survey of recent developments in multiobjective optimization. Ann. Oper. Res. 2007;154:29–50.
- Fliege J, Svaiter BF. Steepest descent methods for multicriteria optimization. Math. Methods Oper. Res. 2000;51:479–494.
- Graña Drummond LM, Svaiter BF. A steepest descent method for vector optimization. J. Comput. Appl. Math. 2005;175:395–414.
- Chuong TD, Yao J-C. Steepest descent methods for critical points in vector optimization problems. Appl. Anal. 2012;91:1811–1829.
- Graña Drummond LM, Iusem AN. A projected gradient method for vector optimization problems. Comput. Optim. Appl. 2004;28:5–29.
- Fukuda EH, Graña Drummond LM. On the convergence of the projected gradient method for vector optimization. Optimization. 2011;60:1009–1021.
- Fukuda EH, Graña Drummond LM. Inexact projected gradient method for vector optimization. Comput. Optim. Appl. 2013;54:473–493.
- Bello Cruz JY, Lucambio Pérez LR, Melo JG. Convergence of the projected gradient method for quasiconvex multiobjective optimization. Nonlinear Anal. 2011;74:5268–5273.
- Fliege J, Graña Drummond LM, Svaiter BF. Newton’s method for multiobjective optimization. SIAM J. Optim. 2009;20:602–626.
- Graña Drummond LM, Raupp FMP, Svaiter BF. A quadratically convergent Newton method for vector optimization. Optimization. 2012. doi:10.1080/02331934.2012.693082. awaiting publication.
- Chuong TD. Newton-like methods for efficient solutions in vector optimization. Comput. Optim. Appl. 2013;54:495–516.
- Qu S, Goh M, Chan FTS. Quasi-Newton methods for solving multiobjective optimization. Oper. Res. Lett. 2011;39:397–399.
- Bonnel H, Iusem AN, Svaiter BF. Proximal methods in vector optimization. SIAM J. Optim. 2005;15:953–970.
- Ceng LC, Yao JC. Approximate proximal methods in vector optimization. European J. Oper. Res. 2007;183:1–19.
- Ceng LC, Mordukhovich BS, Yao JC. Hybrid approximate proximal method with auxiliary variational inequality for vector optimization. J. Optim. Theory Appl. 2010;146:267–303.
- Chuong TD, Mordukhovich BS, Yao JC. Hybrid approximate proximal algorithms for efficient solutions in vector optimization. J. Nonlinear Convex Anal. 2011;12:257–286.
- Rockafellar RT. Convex analysis. Princeton, NJ: Princeton University Press; 1970.
- Miglierina E. Slow solutions of a differential inclusion and vector optimization. Set-Valued Anal. 2004;12:345–356.
- Miglierina E, Molho E, Rocca M. Critical points index for vector functions and vector optimization. J. Optim. Theory Appl. 2008;138:479–496.
- Chen CR. Hölder continuity of the unique solution to parametric vector quasiequilibrium problems via nonlinear scalarization. Positivity. 2013;17:133–150.
- Zălinescu C. Convex analysis in general vector spaces. Singapore: World Scientific; 2002.