Abstract
The proximal point method for a special class of nonconvex multiobjective functions is studied in this paper. We show that the method is well defined and that the accumulation points of any generated sequence, if any, are Pareto–Clarke critical points. Moreover, under additional assumptions, we show the full convergence of the generated sequence.
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Apolinário, H.C.F., Papa Quiroz, E.A., Oliveira, P.R.: A scalarization proximal point method for quasiconvex multiobjective minimization. J. Glob. Optim. 64(1), 79–96 (2016)
Bao, T.Q., Mordukhovich, B.S.: Relative Pareto minimizers in multiobjective optimization: existence and optimality conditions. Math. Program. 122, 301–347 (2010)
Bao, T.Q., Mordukhovich, B.S.: Necessary conditions for super minimizers in constrained multiobjective optimization. J. Glob. Optim. 43, 533–552 (2009)
Bento, G.C., Cruz Neto, J.X., Soubeyran, A.: A proximal point-type method for multicriteria optimization. Set-Valued Var. Anal. 22(3), 557–573 (2014)
Bertsekas, D.P.: Convex Analysis and Optimization. Athena Scientific, Belmont (2003)
Bonnel, H., Iusem, A.N., Svaiter, B.F.: Proximal methods in vector optimization. SIAM J. Optim. 15(4), 953–970 (2005)
Ceng, L.C., Mordukhovich, B.S., Yao, J.C.: Hybrid approximate proximal method with auxiliary variational inequality for vector optimization. J. Optim. Theory Appl. 146(2), 267–303 (2010)
Ceng, L.C., Yao, J.C.: Approximate proximal methods in vector optimization. Eur. J. Oper. Res. 183(1), 1–19 (2007)
Chuong, T.D., Mordukhovich, B.S., Yao, J.C.: Hybrid approximate proximal algorithms for efficient solutions in vector optimization. J. Nonlinear Convex Anal. 12(2), 257–286 (2011)
Clarke, F.H.: Optimization and Nonsmooth Analysis, Volume 5 of Classics in Applied Mathematics, 2nd edn. Society for Industrial and Applied Mathematics (SIAM), Philadelphia (1990)
Custódio, A.L., Madeira, J.F.A., Vaz, A.I.F., Vicente, L.N.: Direct multisearch for multiobjective optimization. SIAM J. Optim. 21(3), 1109–1140 (2011)
Fukushima, M., Mine, H.: A generalized proximal point algorithm for certain nonconvex minimization problems. Int. J. Syst. Sci. 12(8), 989–1000 (1981)
Gal, T., Hanne, T.: On the development and future aspects of vector optimization and MCDM. A tutorial. In: Multicriteria Analysis (Coimbra, 1994), pp. 130–145. Springer, Berlin (1997)
Grad, S.M., Pop, E.L.: Vector duality for convex vector optimization problems by means of the quasi-interior of the ordering cone. Optimization 63(1), 21–37 (2014)
Kaplan, A., Tichatschke, R.: Proximal point methods and nonconvex optimization. J. Glob. Optim. 13(4), 389–406 (1998)
Luc, D.T.: Theory of Vector Optimization, volume 319 of Lecture Notes in Economics and Mathematical Systems. Springer, Berlin (1989)
Mäkelä, M.M., Neittaanmäki, P.: Nonsmooth Optimization. World Scientific Publishing Co., Inc., River Edge (1992)
Mordukhovich, B.S.: Variational Analysis and Generalized Differentiation, II: Applications. Grundlehren Series in Fundamental Principles of Mathematical Sciences, vol. 331. Springer, Berlin (2006)
Rockafellar, R.T.: Convex Analysis. Princeton Mathematical Series, No. 28. Princeton University Press, Princeton (1970)
Villacorta, K.D.V., Oliveira, P.R.: An interior proximal method in vector optimization. Eur. J. Oper. Res. 214(3), 485–492 (2011)
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The work was supported by CAPES and CNPq.
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Bento, G.C., Ferreira, O.P. & Sousa Junior, V.L. Proximal point method for a special class of nonconvex multiobjective optimization functions. Optim Lett 12, 311–320 (2018). https://doi.org/10.1007/s11590-017-1114-0
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DOI: https://doi.org/10.1007/s11590-017-1114-0