MOBOpt — multi-objective Bayesian optimization

Volume: 12, Pages: 100520 - 100520
Published: Jul 1, 2020
Abstract
This work presents a new software, programmed as a Python class, that implements a multi-objective Bayesian optimization algorithm. The proposed method is able to calculate the Pareto front approximation of optimization problems with fewer objective functions evaluations than other methods, which makes it appropriate for costly objectives. The software was extensively tested on benchmark functions for optimization, and it was able to obtain...
Paper Details
Title
MOBOpt — multi-objective Bayesian optimization
Published Date
Jul 1, 2020
Journal
Volume
12
Pages
100520 - 100520
Citation AnalysisPro
  • Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
  • Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.