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Asymptotic analysis in convex composite multiobjective optimization problems

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  • Zhe Chen

Abstract

In this paper, we present a unified approach for studying convex composite multiobjective optimization problems via asymptotic analysis. We characterize the nonemptiness and compactness of the weak Pareto optimal solution sets for a convex composite multiobjective optimization problem. Then, we employ the obtained results to propose a class of proximal-type methods for solving the convex composite multiobjective optimization problem, and carry out their convergence analysis under some mild conditions. Copyright Springer Science+Business Media New York 2013

Suggested Citation

  • Zhe Chen, 2013. "Asymptotic analysis in convex composite multiobjective optimization problems," Journal of Global Optimization, Springer, vol. 55(3), pages 507-520, March.
    • Handle: RePEc:spr:jglopt:v:55:y:2013:i:3:p:507-520
    DOI: 10.1007/s10898-012-0032-z
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    References listed on IDEAS

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    1. Zhe Chen, 2011. "Generalized viscosity approximation methods in multiobjective optimization problems," Computational Optimization and Applications, Springer, vol. 49(1), pages 179-192, May.
    2. S. Deng, 2009. "Characterizations of the Nonemptiness and Boundedness of Weakly Efficient Solution Sets of Convex Vector Optimization Problems in Real Reflexive Banach Spaces," Journal of Optimization Theory and Applications, Springer, vol. 140(1), pages 1-7, January.
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    Cited by:

    1. Rocha, Rogério Azevedo & Oliveira, Paulo Roberto & Gregório, Ronaldo Malheiros & Souza, Michael, 2016. "Logarithmic quasi-distance proximal point scalarization method for multi-objective programming," Applied Mathematics and Computation, Elsevier, vol. 273(C), pages 856-867.

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