Abstract
In this paper, we present two inexact scalarization proximal point methods to solve quasiconvex multiobjective minimization problems on Hadamard manifolds. Under standard assumptions on the problem, we prove that the two sequences generated by the algorithms converge to a Pareto critical point of the problem and, for the convex case, the sequences converge to a weak Pareto solution. Finally, we explore an application of the method to demand theory in economy, which can be dealt with using the proposed algorithm.
Similar content being viewed by others
References
Ehrgot, M.: Multicriteria Optimization, 2nd edn. Springer, Berlin (2005)
Miettinen, K.: Nonlinear Multiobjective Optimization. Springer, Berlin (1998)
Graziano, M.G.: Fuzzy cooperative behavior in response to market imperfections. Int. J. Intell. Syst. 27, 108–131 (2012)
Graziano, M.G., Romaniello, M.: Linear cost share equilibria and the veto power of the grand coalition. Soc. Choice Welf. 38, 269–303 (2012)
Fliege, J.: An efficient interior-point method for convex multicriteria optimization problems. Math. Oper. Res. 31, 825–845 (2006)
Graña Drummond, L.M., Iusem, A.N.: A projected gradient method for vector optimization problems. Comput. Optim. Appl. 28, 5–30 (2008)
Fliege, J., Svaiter, B.F.: Steepest descent methods for multicriteria optimization. Math. Methods Oper. Res. 51, 479–494 (2000)
Gregório, R., Oliveira, P.R.: A logarithmic-quadratic proximal point scalarization method for multiobjective programming. J. Glob. Optim. 49(2), 281–291 (2011)
Rocha, R.A., Oliveira, P.R., Gregório, R.M., Souza, M.: Logarithmic quasi-distance proximal point scalarization method for multi-objective programming. Appl. Math. Comput. 273, 856–867 (2016)
Custódio, A.L., Aguilar Madeira, J.F., Vaz, A.I.F., Vicente, L.N.: Direct multisearch for multiobjective optimization. SIAM J. Optim. 21(3), 1109–1140 (2011)
Rockafellar, R.T.: Monotone operators and the proximal point algorithm. SIAM J. Control Optim. 14(5), 877–898 (1976)
Bonnel, H., Iusem, A.N., Svaiter, B.F.: Proximal methods in vector optimization. SIAM J. Optim. 15(4), 953–970 (2005)
Ceng, L.C., Yao, J.C.: Approximate proximal methods in vector optimization. Eur. J. Oper. Res. 183, 1–19 (2007)
Apolinario, H.C.F., Papa Quiroz, E.A., Oliveira, P.R.: A scalarization proximal point method for quasiconvex multiobjective minimization. J. Global Optim. 64(1), 79–96 (2016)
da Cruz Neto, J.X., da Silva, G.J.P., Ferreira, O.P., Lopes, J.O.: A subgradient method for multiobjective optimization. Comput. Optim. Appl. 54(3), 461–472 (2013)
Bello Cruz, J.Y., Lucambio Pérez, L.R., Melo, J.G.: Convergence of the projected gradient method for quasiconvex multiobjective optimization. Nonlinear Anal. Theory Methods Appl. 74(16), 5268–5273 (2011)
Li, H.L., Yu, C.S.: Solving multiple objective quasiconvex goal programming problems by linear programming. Int. Trans. Oper. Res. 7(3), 265–284 (2000)
do Carmo, M.P.: Riemannian Geometry. Bikhausen, Boston (1992)
Udriste, C.: Convex Function and Optimization Methods on Riemannian Manifolds. Kluwer Academic Publishers, Berlin (1994)
Sakai, T.: Riemannian Geometry. American Mathematical Society, Providence (1996)
Rapcsák, T.: Smooth Nonlinear Optimization in \(\mathbb{R}^n\). Kluwer Academic Publishers, Berlin (1997)
Bento, G.C., Barbosa, S.D., Da Cruz Neto, X.J., Oliveira, P.R., Souza, J.C.: Computing Riemannian center of mass on Hadamard manifolds. J. Optim. Theory Appl. 183, 977–992 (2019)
Nesterov, Y.E., Todd, M.J.: On the Riemannian geometry defined by concordant barrier and interior-point methods. Found. Comput. Math. 2, 333–361 (2002)
Rothaus, O.S.: Domains of Positivity. Abh. Math. Sem. Univ. Hamburg 24, 189–235 (1960)
Papa Quiroz, E.A., Oliveira, P.R.: Full convergence of the proximal point method for quasiconvex function on Hadamard manifolds, ESAIM: Control. Optim. Calculus Variations 18(2), 483–500 (2012)
Papa Quiroz, E.A., Oliveira, P.R.: New results on linear optimization through diagonal metrics and riemannian geometry tools, technical report, ES-645/04. Federal University of Rio de Janeiro, Pesc Coppe (2004)
Bento, G.C., Ferreira, O.P., Oliveira, P.R.: Unconstrained steepest descent method for multicriteria optimization on Riemannian manifolds. J. Optim. Theory Appl. 154(1), 88–107 (2012)
Bento, G.C., Cruz Neto, J.X.: A subgradient method for multiobjective optimization on Riemannian manifolds. J. Optim. Theory Appl. 159(1), 125–137 (2013)
Bento, G.C., Cruz Neto, J.X., Santos, P.S.M.: An inexact steepest descent method for multicriteria optimization on Riemannian manifolds. J. Optim. Theory Appl. 159, 108–124 (2013)
Bento, G.C., Cruz Neto, J.X., Meireles, L.: Proximal point method for locally Lipschitz fumction in multiobjective optimization of Hadamard manifolds. J. Optim. Theory Appl. 179, 37–52 (2018)
Baygorrea, N., Papa Quiroz, E.A., Maculan, N.: Inexact proximal point methods for quasiconvex minimization on Hadamard manifolds. J. Oper. Res. Soc. China 4(4), 397–424 (2016)
Baygorrea, N., Papa Quiroz, E.A., Maculan, N.: On the convergence rate of an inexact proximal point algorithm for quasiconvex minimization on Hadamard manifolds. J. Oper. Res. Soc. China 5(4), 457–467 (2017)
Papa Quiroz, E.A., Baygorrea, N., Maculan, N.: Clarke Subdifferential, Pareto-Clarke critical points and descent directions to multiobjective optimization on Hadamard manifolds Submitted
da Cruz Neto, J.X., de Lima, L.L., Oliveira, P.R.: Geodesic algorithms in Riemannian geometry. Balkan J. Geometry Appl. 3(2), 89–100 (1998)
Ferreira, O.P., Oliveira, P.R.: Proximal point algorithm on Riemannian manifolds. Optimization 51(2), 257–270 (2002)
Bento, G.C., Ferreira, O.P., Oliveira, P.R.: Local convergence of the proximal point method for a special class of nonconvex functions on Hadamard manifolds. Nonlinear Anal. Theory Methods Appl. 73(2), 564–572 (2010)
Huang, X.X., Yang, X.Q.: Duality for multiobjective optimization via nonlinear Lagrangian functions. J. Optim. Theory Appl. 120(1), 111–127 (2004)
Villacorta, K.D.V., Oliveira, P.R.: An interior proximal method in vector optimization. Eur. J. Oper. Res. 214, 485–492 (2011)
Papa Quiroz, E.A., Oliveira, P.R.: Proximal point methods for minimizing quasiconvex locally lipschitz functions on Hadamard manifolds. Nonlinnear Anal. 75(15), 5924–5932 (2012)
Tang, G.J., Huang, N.J.: An inexact proximal point algorithm for maximal monotone vector fields on Hadamard manifolds. Oper. Res. Lett. 6(41), 586–591 (2013)
Polyak, B.: Introduction to optimization Translations Series in Mathematics and Engineering. Springer, New York (1987)
Papa Quiroz, E.A., Oliveira, P.R.: Proximal point methods for quasiconvex and convex functions with Bregman distances on Hadamard manifolds. J. Convex Anal. 16(1), 49–69 (2009)
Lang, S.: Fundamentals of Differential Geometry: Graduate Text in Mathematics 191. Springer, Berlin (1998)
Attouch, H., Soubeyran, A.: Local search proximal algorithms as decision dynamics with costs to move. Set-valued Var. Anal. 19(1), 157–177 (2011)
Tang, F.M., Huang, P.L.: On the convergence rate of a proximal point algorithm for vector functions on Hadamard manifolds. J. Oper. Res. Soc. China 5(3), 405–417 (2017)
Author information
Authors and Affiliations
Corresponding author
Additional information
Communicated by Alexandru Kristály.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Papa Quiroz, E.A., Baygorrea Cusihuallpa, N. & Maculan, N. Inexact Proximal Point Methods for Multiobjective Quasiconvex Minimization on Hadamard Manifolds. J Optim Theory Appl 186, 879–898 (2020). https://doi.org/10.1007/s10957-020-01725-7
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10957-020-01725-7
Keywords
- Proximal point methods
- Quasiconvex function
- Hadamard manifolds
- Multiobjective optimization
- Pareto optimality