Catching-Up Algorithm with Approximate Projections for Moreau’s Sweeping Processes
Juan Guillermo Garrido () and
Emilio Vilches ()
Additional contact information
Juan Guillermo Garrido: Universidad de Chile
Emilio Vilches: Universidad de O’Higgins
Journal of Optimization Theory and Applications, 2024, vol. 203, issue 2, No 4, 1160-1187
Abstract:
Abstract In this paper, we develop an enhanced version of the catching-up algorithm for sweeping processes through an appropriate concept of approximate projection. We establish some properties of this notion of approximate projection. Then, under suitable assumptions, we show the convergence of the enhanced catching-up algorithm for prox-regular, subsmooth, and merely closed sets. Finally, we briefly discuss some efficient numerical methods for obtaining approximate projections. Our results recover classical existence results in the literature and provide new insights into the numerical simulation of sweeping processes.
Keywords: Sweeping process; Differential inclusions; Approximate projections; 34A60; 49J52; 34G25; 49J53 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://link.springer.com/10.1007/s10957-024-02407-4 Abstract (text/html)
Access to the full text of the articles in this series is restricted.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:joptap:v:203:y:2024:i:2:d:10.1007_s10957-024-02407-4
Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/10957/PS2
DOI: 10.1007/s10957-024-02407-4
Access Statistics for this article
Journal of Optimization Theory and Applications is currently edited by Franco Giannessi and David G. Hull
More articles in Journal of Optimization Theory and Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().