VOPy: A Framework for Black-box Vector Optimization

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Opis bibliograficzny
Wydane w:arXiv.org (Dec 9, 2024), p. n/a
1. autor: Yaşar, Cahit Yıldırım
Kolejni autorzy: Efe Mert Karagözlü, İlter Onat Korkmaz, Ararat, Çağın, Tekin, Cem
Wydane:
Cornell University Library, arXiv.org
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022 |a 2331-8422 
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045 0 |b d20241209 
100 1 |a Yaşar, Cahit Yıldırım 
245 1 |a VOPy: A Framework for Black-box Vector Optimization 
260 |b Cornell University Library, arXiv.org  |c Dec 9, 2024 
513 |a Working Paper 
520 3 |a We introduce VOPy, an open-source Python library designed to address black-box vector optimization, where multiple objectives must be optimized simultaneously with respect to a partial order induced by a convex cone. VOPy extends beyond traditional multi-objective optimization (MOO) tools by enabling flexible, cone-based ordering of solutions; with an application scope that includes environments with observation noise, discrete or continuous design spaces, limited budgets, and batch observations. VOPy provides a modular architecture, facilitating the integration of existing methods and the development of novel algorithms. We detail VOPy's architecture, usage, and potential to advance research and application in the field of vector optimization. The source code for VOPy is available at https://github.com/Bilkent-CYBORG/VOPy. 
653 |a Algorithms 
653 |a Python 
653 |a Source code 
653 |a Black boxes 
653 |a Multiple objective analysis 
653 |a Optimization 
700 1 |a Efe Mert Karagözlü 
700 1 |a İlter Onat Korkmaz 
700 1 |a Ararat, Çağın 
700 1 |a Tekin, Cem 
773 0 |t arXiv.org  |g (Dec 9, 2024), p. n/a 
786 0 |d ProQuest  |t Engineering Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3142733997/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch 
856 4 0 |3 Full text outside of ProQuest  |u http://arxiv.org/abs/2412.06604