Exact extension of the DIRECT algorithm to multiple objectives
Abstract
The direct algorithm has been recognized as an efficient global optimization method which has few requirements of regularity and has proven to be globally convergent in general cases. direct has been an inspiration or has been used as a component for many multiobjective optimization algorithms. We propose an exact and as genuine as possible extension of the direct method for multiple objectives, providing a proof of global convergence (i.e., a guarantee that in an infinite time the algorithm becomes everywhere dense). We test the efficiency of the algorithm on a nonlinear and nonconvex vector function.
Main Authors
Format
Conferences
Conference paper
Published
2019
Series
Subjects
Publication in research information system
Publisher
American Institute of Physics
The permanent address of the publication
https://urn.fi/URN:NBN:fi:jyu-201905292875Use this for linking
Parent publication ISBN
978-0-7354-1798-4
Review status
Peer reviewed
ISSN
0094-243X
DOI
https://doi.org/10.1063/1.5090020
Conference
International Global Optimization Workshop
Language
English
Published in
AIP Conference Proceedings
Is part of publication
LeGO 2018 : Proceedings of the 14th International Global Optimization Workshop
Citation
- Lovison, A., & Miettinen, K. (2019). Exact extension of the DIRECT algorithm to multiple objectives. In M. T. M. Emmerich, A. H. Deutz, S. C. Hille, & Y. D. Sergeyev (Eds.), LeGO 2018 : Proceedings of the 14th International Global Optimization Workshop (Article 020053). American Institute of Physics. AIP Conference Proceedings, 2070. https://doi.org/10.1063/1.5090020
License
Funder(s)
Research Council of Finland
Funding program(s)
Akatemiahanke, SA
Academy Project, AoF
Additional information about funding
This research was partly funded by the Academy of Finland (grant no. 287496).
Copyright© 2019 Author(s).