Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/128926
Citations | ||
Scopus | Web of Science® | Altmetric |
---|---|---|
?
|
?
|
Type: | Conference paper |
Title: | Runtime analysis of evolutionary multi-objective algorithms optimising the degree and diameter of spanning trees |
Author: | Gao, W. Pourhassan, M. Roostapour, V. Neumann, F. |
Citation: | Lecture Notes in Artificial Intelligence, 2019 / Deb, K., Goodman, E.D., Coello, C.A.C., Klamroth, K., Miettinen, K., Mostaghim, S., Reed, P.M. (ed./s), vol.11411, pp.504-515 |
Publisher: | Springer |
Publisher Place: | Cham, Switzerland |
Issue Date: | 2019 |
Series/Report no.: | Lecture Notes in Computer Science; 11411 |
ISBN: | 3030125971 9783030125974 |
ISSN: | 0302-9743 1611-3349 |
Conference Name: | 10th International Conference on Evolutionary Multi-Criterion Optimization (EMO) (10 Mar 2019 - 13 Mar 2019 : East Lansing, USA) |
Editor: | Deb, K. Goodman, E.D. Coello, C.A.C. Klamroth, K. Miettinen, K. Mostaghim, S. Reed, P.M. |
Statement of Responsibility: | Wanru Gao, Mojgan Pourhassan, Vahid Roostapour, and Frank Neumann |
Abstract: | Motivated by the telecommunication network design, we study the problem of finding diverse set of minimum spanning trees of a certain complete graph based on the two features which are maximum degree and diameter. In this study, we examine a simple multi-objective EA, GSEMO, in solving the two problems where we maximise or minimise the two features at the same time.With a rigorous runtime analysis, we provide understanding of how GSEMO optimize the set of minimum spanning trees in these two different feature spaces. |
Keywords: | Evolutionary multi-objective optimisation; Algorithm analysis |
Rights: | © Springer Nature Switzerland AG 2019 |
DOI: | 10.1007/978-3-030-12598-1_40 |
Grant ID: | http://purl.org/au-research/grants/arc/DP160102401 |
Published version: | https://link.springer.com/book/10.1007/978-3-030-12598-1 |
Appears in Collections: | Aurora harvest 4 Computer Science publications |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
hdl_128926.pdf | Accepted version | 369.42 kB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.