Convergence and complexity guarantees for a wide class of descent algorithms in nonconvex multi-objective optimization
Matteo Lapucci
| Year of publication: |
2024
|
|---|---|
| Authors: | Lapucci, Matteo |
| Published in: |
Operations research letters : a journal of INFORMS devoted to the rapid publication of concise contributions in operations research. - Amsterdam [u.a.] : Elsevier Science, ISSN 0167-6377, ZDB-ID 1467065-3. - Vol. 54.2024, Art.-No. 107115, p. 1-8
|
| Subject: | Descent algorithms | Global convergence | Multi-objective optimization | Steepest-descent-related | Worst-case complexity | Theorie | Theory | Mathematische Optimierung | Mathematical programming | Multikriterielle Entscheidungsanalyse | Multi-criteria analysis | Algorithmus | Algorithm |
Online Resource
| Type of publication: | Article |
|---|---|
| Type of publication (narrower categories): | Aufsatz in Zeitschrift ; Article in journal |
| Language: | English |
| Other identifiers: | 10.1016/j.orl.2024.107115 [DOI] |
| Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10015049301