A research-style project that solves the mean-variance portfolio optimization problem with a cardinality constraint using integer programming. This model captures the real-world need to limit the number of assets in a portfolio, introducing combinatorial complexity and paving the way for quantum-inspired methods.
A continuous local search SAT solver based on Fourier expansion for hybrid Boolean constraints.
High Dimensional Portfolio Selection with Cardinality Constraints
A research-style project that solves the mean-variance portfolio optimization problem with a cardinality constraint using integer programming. This model captures the real-world need to limit the number of assets in a portfolio, introducing combinatorial complexity and paving the way for quantum-inspired methods.
Extensions of DiGress for molecular graph generation with logical constraints, focusing on Lipinski’s Rule of Five.
This project addresses the real-world portfolio optimization problem, going beyond classical mean-variance models. Actual portfolio construction involves discrete investment decisions, transaction costs, and monitoring constraints, making the problem a Mixed-Integer Optimization (MIO) challenge that is computationally intractable at scale
🎊 Repo for code related to a syllogistic logic of 'all', 'at least', and 'more than'. Includes code for model construction and use of prover9 to explore the proof rules of the system.
A model-based algorithm for the fair-capacitated clustering problem
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