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Multiibjective optimization : an inertial dynamical approach to Pareto optima

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arxiv 1506.02823 v1 pith:HQ7XMXXE submitted 2015-06-09 math.OC

Hédy Attouch (I3M) , Guillaume Garrigos (UTFSM , I3M) This is my paper · ORCID
classification math.OC
keywords optimizationapproachfirstinertialmulti-objectiveparetocaseconcerning
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We present some first results concerning a gradient-based dynamic approach to multi-objective optimization problems, involving inertial effects. We prove the existence of global solution trajectories for this second-order differential equation, and their convergence to weak Pareto points in the convex case. It is a first step towards the design of fast numerical methods for multi-objective optimization.

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  1. Accelerated Multiple Wasserstein Gradient Flows for Multi-objective Distributional Optimization

    cs.LG 2026-01 conditional novelty 6.0 of 10

    A-MWGraD accelerates multi-objective Wasserstein gradient descent, achieving O(1/t^2) and exponential merit-function convergence rates in continuous time for convex and strongly convex objectives.

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