---
res:
bibo_abstract:
- The efficient optimization method for locally Lipschitz continuous multiobjective
optimization problems from [1] is extended from finite-dimensional problems to
general Hilbert spaces. The method iteratively computes Pareto critical points,
where in each iteration, an approximation of the subdifferential is computed in
an efficient manner and then used to compute a common descent direction for all
objective functions. To prove convergence, we present some new optimality results
for nonsmooth multiobjective optimization problems in Hilbert spaces. Using these,
we can show that every accumulation point of the sequence generated by our algorithm
is Pareto critical under common assumptions. Computational efficiency for finding
Pareto critical points is numerically demonstrated for multiobjective optimal
control of an obstacle problem.@eng
bibo_authorlist:
- foaf_Person:
foaf_givenName: Konstantin
foaf_name: Sonntag, Konstantin
foaf_surname: Sonntag
foaf_workInfoHomepage: http://www.librecat.org/personId=56399
orcid: https://orcid.org/0000-0003-3384-3496
- foaf_Person:
foaf_givenName: Bennet
foaf_name: Gebken, Bennet
foaf_surname: Gebken
foaf_workInfoHomepage: http://www.librecat.org/personId=32643
- foaf_Person:
foaf_givenName: Georg
foaf_name: Müller, Georg
foaf_surname: Müller
- foaf_Person:
foaf_givenName: Sebastian
foaf_name: Peitz, Sebastian
foaf_surname: Peitz
foaf_workInfoHomepage: http://www.librecat.org/personId=47427
orcid: 0000-0002-3389-793X
- foaf_Person:
foaf_givenName: Stefan
foaf_name: Volkwein, Stefan
foaf_surname: Volkwein
dct_date: 2024^xs_gYear
dct_language: eng
dct_title: A Descent Method for Nonsmooth Multiobjective Optimization in Hilbert
Spaces@
...