Convergence of a steepest descent algorithm in shape optimisation using W^1,∞ functions

¹ Otto-von-Guericke-University Magdeburg, Department of Mathematics, Universitätsplatz 2, 39106 Magdeburg, Germany
² Department of Mathematics, University of Sussex, Brighton BN1 9RF, UK
³ Mathematical Institute, University of Koblenz, Universitätsstr. 1, 56070 Koblenz, Germany

Received: 23 October 2023
Accepted: 11 April 2025

Abstract

Built upon previous work of the authors in Deckelnick et al. [ESAIM: COCV 28 (2022) 2], we present a general shape optimisation framework based on the method of mappings in the W^1,∞ topology together with a suitable finite element discretisation. For the numerical solution of the respective discrete shape optimisation problems we propose a steepest descent minimisation algorithm with Armijo-Goldstein stepsize rule. We show that the sequence generated by this descent method globally converges, and under appropriate assumptions also, that every accumulation point of this sequence is a stationary point of the shape functional. Moreover, for the mesh discretisation parameter tending to zero we under appropriate assumptions prove convergence of the discrete stationary shapes in the Hausdorff complementary metric. To illustrate our approach we present a selection of numerical examples for PDE constrained shape optimisation problems, where we include numerical convergence studies which support our analytical findings.