Branch and probability bound methods in multi-objective optimization

Z̆ilinskas, Antanas and Zhigljavsky, Anatoly Alexandrovich ORCID: https://orcid.org/0000-0003-0630-8279 2016. Branch and probability bound methods in multi-objective optimization. Optimization Letters 10 (2) , pp. 341-353. 10.1007/s11590-014-0777-z

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Abstract

An approach to non-convex multi-objective optimization problems is considered where only the values of objective functions are required by the algorithm. The proposed approach is a generalization of the probabilistic branch-and-bound approach well applicable to complicated problems of single-objective global optimization. In the present paper the concept of probabilistic branch-and-bound based multi-objective optimization algorithms is discussed, and some illustrations are presented.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Mathematics
Subjects:	Q Science > QA Mathematics
Publisher:	Springer
ISSN:	1862-4472
Date of Acceptance:	29 July 2014
Last Modified:	01 Nov 2022 09:56
URI:	https://orca.cardiff.ac.uk/id/eprint/89728

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