eprintid: 14043
rev_number: 6
eprint_status: archive
userid: 5
dir: disk0/00/01/40/43
datestamp: 2016-12-01 10:38:58
lastmod: 2021-08-27 17:41:40
status_changed: 2016-12-01 10:38:58
type: book_section
metadata_visibility: show
item_issues_count: 1
creators_name: Lemarechal, C.
creators_id: AL0228
title: Optimisation non Differentiable: Methodes de Faisceaux
ispublished: pub
divisions: prog_pop
abstract: We define a class of descent methods to minimize a nondifferentiable function. These methods are based on a representation of the objective which combines a quadratic approximation and the usual approximation by a piecewise linear function. Hence, they realize a synthesis between quasi-Newton methods and cutting plane methods. In addition, they have the particularity of requiring no sophisticated line search. They are also presented in ref. [7] (in English).
date: 2006
date_type: published
publisher: Springer Berlin Heidelberg
id_number: 10.1007/BFb0063614
creators_browse_id: 2110
full_text_status: none
series: Lecture Notes in Mathematics
volume: 704
place_of_pub: Germany
pagerange: 53-61
refereed: TRUE
isbn: 978-3-540-35411-6
issn: 0075-8434
book_title: Computing Methods in Applied Sciences and Engineering, 1977, I
editors_name: Glowinski, R.
editors_name: Lions, J.L.
editors_name: Liboria, I.
coversheets_dirty: FALSE
fp7_type: info:eu-repo/semantics/bookPart
citation:   Lemarechal, C. <https://pure.iiasa.ac.at/view/iiasa/2110.html>  (2006).  Optimisation non Differentiable: Methodes de Faisceaux.    In:  Computing Methods in Applied Sciences and Engineering, 1977, I. Eds. Glowinski, R., Lions, J.L., & Liboria, I., pp. 53-61 Germany: Springer Berlin Heidelberg.  ISBN 978-3-540-35411-6 10.1007/BFb0063614 <https://doi.org/10.1007/BFb0063614>.