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• W1992296912 abstract "In a general Hilbert framework, we consider continuous gradient-like dynamical systems for constrained multiobjective optimization involving non-smooth convex objective functions. Our approach is in the line of a previous work where was considered the case of convex di erentiable objective functions. Based on the Yosida regularization of the subdi erential operators involved in the system, we obtain the existence of strong global trajectories. We prove a descent property for each objective function, and the convergence of trajectories to weak Pareto minima. This approach provides a dynamical endogenous weighting of the objective functions. Applications are given to cooperative games, inverse problems, and numerical multiobjective optimization." @default.
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• W1992296912 date "2015-02-01" @default.
• W1992296912 modified "2023-09-27" @default.
• W1992296912 title "A dynamic gradient approach to Pareto optimization with nonsmooth convex objective functions" @default.
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• W1992296912 doi "https://doi.org/10.1016/j.jmaa.2014.09.001" @default.
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