We combine Mixed-Integer Programming (MIP) with Machine Learning to find near-optimal portfolios efficiently: maximize: μᵀw - λ·(wᵀΣw) - transaction_costs(w ...
Our approach introduces the first general Learning-to-Optimize (L2O) framework designed for Mixed-Integer Nonlinear Programming (MINLP). As illustrated above, the approach consists of two core ...
Abstract: The rapid evolution of artificial intelligence and IoT (Internet of Things) technology is making autonomous driving an emerging critical trend in open-pit mining operations. However, current ...
Integer programming is a crucial branch of mathematical optimisation that focuses on problems where some or all decision variables are constrained to be integers. This field underpins many practical ...
Abstract: Green hydrogen is increasingly considered a cornerstone of clean energy, though it remains more expensive than hydrogen derived from fossil fuels. This study introduces a mixed-integer ...
ABSTRACT: This article examines some of the properties of quasi-Fejer sequences when used in quasi-gradiental techniques as an alternative to stochastic search techniques for optimizing unconstrained ...
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