Chain Rules for a Proper \(\varepsilon \) -Subdifferential of Vector Mappings
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  • 作者:César Gutiérrez ; Lidia Huerga ; Vicente Novo…
  • 关键词:Vector optimization ; Proper $$\varepsilon $$ ε ; efficiency ; Proper $$\varepsilon $$ ε ; subdifferential ; Strong $$\varepsilon $$ ε ; efficiency ; Strong $$\varepsilon $$ ε ; subdifferential ; Nearly cone ; subconvexlikeness ; Linear scalarization ; 90C48 ; 90C25 ; 90C29 ; 49J52 ; 49K27
  • 刊名:Journal of Optimization Theory and Applications
  • 出版年:2015
  • 出版时间:November 2015
  • 年:2015
  • 卷:167
  • 期:2
  • 页码:502-526
  • 全文大小:575 KB
  • 参考文献:1.Gutiérrez, C., Huerga, L., Jiménez, B., Novo, V.: Proper approximate solutions and \(\varepsilon \) -subdifferentials in vector optimization: Basic properties and limit behaviour. Nonlinear Anal. 79, 52-7 (2013)MATH MathSciNet CrossRef
    2.Gutiérrez, C., Huerga, L., Novo, V.: Scalarization and saddle points of approximate proper solutions in nearly subconvexlike vector optimization problems. J. Math. Anal. Appl. 389, 1046-058 (2012)MATH MathSciNet CrossRef
    3.Gao, Y., Yang, X., Teo, K.L.: Optimality conditions for approximate solutions of vector optimization problems. J. Ind. Manag. Optim. 7, 483-96 (2011)MATH MathSciNet CrossRef
    4.Gutiérrez, C., Jiménez, B., Novo, V.: On approximate efficiency in multiobjective programming. Math. Methods Oper. Res. 64, 165-85 (2006)MATH MathSciNet CrossRef
    5.Gutiérrez, C., Jiménez, B., Novo, V.: A unified approach and optimality conditions for approximate solutions of vector optimization problems. SIAM J. Optim. 17, 688-10 (2006)MATH MathSciNet CrossRef
    6.Gutiérrez, C., Huerga, L., Jiménez, B., Novo, V.: Proper approximate solutions and \(\varepsilon \) -subdifferentials in vector optimization: Moreau–Rockafellar type theorems. J. Convex Anal. 21, 857-86 (2014)MATH MathSciNet
    7.El Maghri, M.: Pareto–Fenchel \(\varepsilon \) -subdifferential sum rule and \(\varepsilon \) -efficiency. Optim. Lett. 6, 763-81 (2012)MATH MathSciNet CrossRef
    8.Tuan, L.A.: \(\varepsilon \) -optimality conditions for vector optimization problems with set-valued maps. Numer. Funct. Anal. Optim. 31, 78-5 (2010)MATH MathSciNet CrossRef
    9.El Maghri, M.: Pareto–Fenchel \(\varepsilon \) -subdifferential composition rule and \(\varepsilon \) -efficiency. Numer. Funct. Anal. Optim. 35, 1-9 (2014)MATH MathSciNet CrossRef
    10.Raffin, C.: Contribution à l’étude des Programmes Convexes Définis dans des Espaces Vectoriels Topologiques. Thèse, Université Pierre et Marie Curie, Paris (1969)
    11.G?pfert, A., Riahi, H., Tammer, C., Z?linescu, C.: Variational Methods in Partially Ordered Spaces. Springer, New York (2003)MATH
    12.Jahn, J.: Vector Optimization. Theory, Applications, and Extensions. Springer, Berlin (2011)MATH
    13.Sawaragi, Y., Nakayama, H., Tanino, T.: Theory of Multiobjective Optimization. Academic Press, Orlando (1985)MATH
    14.Rong, W.: Proper \(\varepsilon \) -efficiency in vector optimization problems with cone-subconvexlikeness. Acta Sci. Natur. Univ. NeiMongol 28, 609-13 (1997)MathSciNet
    15.Kutateladze, S.S.: Convex \(\varepsilon \) -programming. Soviet Math. Dokl. 20, 391-93 (1979)MATH
    16.Br?ndsted, A., Rockafellar, R.T.: On the subdifferentiability of convex functions. Proc. Am. Math. Soc. 16, 605-11 (1965)CrossRef
    17.Yang, X.M., Li, D., Wang, S.Y.: Near-subconvexlikeness in vector optimization with set-valued functions. J. Optim. Theory Appl. 110, 413-27 (2001)MATH MathSciNet CrossRef
    18.Borwein, J.: Proper efficient points for maximizations with respect to cones. SIAM J. Control Optim. 15, 57-3 (1977)MATH CrossRef
    19.El Maghri, M., Laghdir, M.: Pareto subdifferential calculus for convex vector mappings and applications to vector optimization. SIAM J. Optim. 19, 1970-994 (2009)MATH CrossRef
    20.Z?linescu, C.: Convex Analysis in General Vector Spaces. World Scientific, Singapore (2002)MATH CrossRef
    21.Hiriart-Urruty, J.-B.: \(\varepsilon \) -subdifferential calculus. Res. Notes Math. 57, 43-2 (1982)MathSciNet
    22.Gutiérrez, C., López, R., Novo, V.: Existence and boundedness of solutions in infinite-dimensional vector optimization problems. J. Optim. Theory Appl. 162, 515-47 (2014)MATH MathSciNet CrossRef
  • 作者单位:César Gutiérrez (1)
    Lidia Huerga (2)
    Vicente Novo (2)
    Lionel Thibault (3)

    1. Universidad de Valladolid, Valladolid, Spain
    2. Universidad Nacional de Educación a Distancia, Madrid, Spain
    3. Université Montpellier 2, Montpellier, France
  • 刊物主题:Calculus of Variations and Optimal Control; Optimization; Optimization; Theory of Computation; Applications of Mathematics; Engineering, general; Operations Research/Decision Theory;
  • 出版者:Springer US
  • ISSN:1573-2878
文摘
In this paper, we derive exact chain rules for a proper epsilon-subdifferential in the sense of Benson of extended vector mappings, recently introduced by ourselves. For this aim, we use a new regularity condition and a new strong epsilon-subdifferential for vector mappings. In particular, we determine chain rules when one of the mappings is linear, obtaining formulations easier to handle in the finite-dimensional case by considering the componentwise order. This Benson proper epsilon-subdifferential generalizes and improves several of the most important proper epsilon-subdifferentials of vector mappings given in the literature and, consequently, the results presented in this work extend known chain rules stated for the last ones. As an application, we derive a characterization of approximate Benson proper solutions of implicitly constrained convex Pareto problems. Moreover, we estimate the distance between the objective values of these approximate proper solutions and the set of nondominated attained values. Keywords Vector optimization Proper \(\varepsilon \)-efficiency Proper \(\varepsilon \)-subdifferential Strong \(\varepsilon \)-efficiency Strong \(\varepsilon \)-subdifferential Nearly cone-subconvexlikeness Linear scalarization

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