VOPy: A Framework for Black-box Vector Optimization

• URL: http://arxiv.org/abs/2412.06604v1
• Date: Mon, 09 Dec 2024 15:53:02 GMT
• Title: VOPy: A Framework for Black-box Vector Optimization
• Authors: Yaşar Cahit Yıldırım, Efe Mert Karagözlü, İlter Onat Korkmaz, Çağın Ararat, Cem Tekin,
• Abstract summary: We introduce VOPy, an open-source Python library designed to address black-box vector optimization. VOPy extends beyond traditional multi-objective optimization tools by enabling flexible, cone-based ordering of solutions. We detail VOPy's architecture, usage, and potential to advance research and application in the field of vector optimization.
• Score: 6.571063542099525
• License:
• Abstract: 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.

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