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Branch and probability bound methods in multi-objective optimization

Z̆ilinskas, Antanas and Zhigljavsky, Anatoly Alexandrovich ORCID: 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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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

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