New Directions in Multi-Objective Optimization with Applications
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Moondra, Jai
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Abstract
This thesis introduces the portfolio framework for optimization with multiple objectives. A portfolio is a small set of solutions that approximately optimizes every objective under consideration. This approach recognizes the inherent plurality of objectives and provides a structured way to navigate competing goals. Instead of insisting on a single `best' solution, portfolios offer a small number of high-quality solutions that together span the space of possible preferences. This work discusses the theoretical foundations, algorithmic techniques, and practical applications of this framework across various problems in machine learning and combinatorial optimization.
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2025-12
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Dissertation (PhD)