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2020 | OriginalPaper | Chapter

A Partition Based Bayesian Multi-objective Optimization Algorithm

Authors : Antanas Žilinskas, Linas Litvinas

Published in: Numerical Computations: Theory and Algorithms

Publisher: Springer International Publishing

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Abstract

The research is aimed at coping with the inherent computational intensity of Bayesian multi-objective optimization algorithms. We propose the implementation which is based on the rectangular partition of the feasible region and circumvents much of computational burden typical for the traditional implementations of Bayesian algorithms. The included results of the solution of testing and practical problems illustrate the performance of the proposed algorithm.

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Title: A Partition Based Bayesian Multi-objective Optimization Algorithm
Authors: Antanas Žilinskas
Linas Litvinas
Publisher: Springer International Publishing
Book: Numerical Computations: Theory and Algorithms
Print ISBN: 978-3-030-40615-8

Electronic ISBN: 978-3-030-40616-5

Copyright Year: 2020
DOI: https://doi.org/10.1007/978-3-030-40616-5_50

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