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Iteration-complexity and asymptotic analysis of steepest descent method for multiobjective optimization on Riemannian manifolds

arXiv 1906.05975 ↗First posted 14 Jun 2019math.OCcited by 1

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Abstract (arXiv)

The steepest descent method for multiobjective optimization on Riemannian manifolds with lower bounded sectional curvature is analyzed in this paper. The aim of the paper is twofold. Firstly, an asymptotic analysis of the method is presented with three different finite procedures for determining the stepsize, namely, Lipschitz stepsize, adaptive stepsize and Armijo-type stepsize. The second aim is to present, by assuming that the Jacobian of the objective function is componentwise Lipschitz continuous, iteration-complexity bounds for the method with these three stepsizes strategies. In addition, some examples are presented to emphasize the importance of working in this new context. Numerical experiments are provided to illustrate the effectiveness of the method in this new setting and certify the obtained theoretical results.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). First posted on arXiv 14 Jun 2019.

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