Abstract
Multiobjective optimization is a useful mathematical model in order to investigate real-world problems with conflicting objectives, arising from economics, engineering, and human decision making. In this paper, a convex composite multiobjective optimization problem, subject to a closed convex constraint set, is studied. New first-order optimality conditions for a weakly efficient solution of the convex composite multiobjective optimization problem are established via scalarization. These conditions are then extended to derive second-order optimality conditions.
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Yang, X.Q., Jeyakumar, V. First and Second-Order Optimality Conditions for Convex Composite Multiobjective Optimization. Journal of Optimization Theory and Applications 95, 209–224 (1997). https://doi.org/10.1023/A:1022695714596
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DOI: https://doi.org/10.1023/A:1022695714596