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https://hdl.handle.net/2440/111349
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Type: | Conference paper |
Title: | Multi-objective optimisation with multiple preferred regions |
Author: | Mahbub, M. Wagner, M. Crema, L. |
Citation: | Lecture Notes in Artificial Intelligence, 2017 / Wagner, M., Li, X., Hendtlass, T. (ed./s), vol.10142, pp.241-253 |
Publisher: | Springer |
Publisher Place: | Cham, Switzerland |
Issue Date: | 2017 |
Series/Report no.: | Lecture Notes in Computer Science; 10142 |
ISBN: | 3319516906 9783319516905 |
ISSN: | 0302-9743 1611-3349 |
Conference Name: | 3rd Australasian Conference on Artificial Life and Computational Intelligence (ACALCI 2017) (31 Jan 2017 - 2 Feb 2017 : Geelong, AUSTRALIA) |
Editor: | Wagner, M. Li, X. Hendtlass, T. |
Statement of Responsibility: | Md. Shahriar Mahbub, Markus Wagner and Luigi Crema |
Abstract: | The typical goal in multi-objective optimization is to find a set of good and well-distributed solutions. It has become popular to focus on specific regions of the objective space, e.g., due to market demands or personal preferences. In the past, a range of different approaches has been proposed to consider preferences for regions, including reference points and weights. While the former technique requires knowledge over the true set of trade-offs (and a notion of “closeness”) in order to perform well, it is not trivial to encode a non-standard preference for the latter. With this article, we contribute to the set of algorithms that consider preferences. In particular, we propose the easy-to-use concept of “preferred regions” that can be used by laypeople, we explain algorithmic modifications of NSGAII and AGE, and we validate their effectiveness on benchmark problems and on a real-world problem. |
Description: | Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 10142) |
Rights: | © Springer International Publishing AG 2017 |
DOI: | 10.1007/978-3-319-51691-2_21 |
Grant ID: | http://purl.org/au-research/grants/arc/DE160100850 |
Published version: | http://www.springer.com/gp/book/9783319516905 |
Appears in Collections: | Aurora harvest 8 Computer Science publications |
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