Or take a look at some advice on streamlining rote, tedious, repetitive tasks. AI can help optimize things like writing emails, generating social media content, working with leads, and more. This is ...

Every enterprise leader has seen the pattern: a proof-of-concept AI tool that impresses in the demo and then three months later, it's hemorrhaging accuracy, choking on edge cases, and nobody can ...

NVIDIA's GPU-accelerated cuOpt engine discovers new solutions for four MIPLIB benchmark problems, outperforming CPU solvers with 22% lower objective gaps. NVIDIA's cuOpt optimization engine has found ...

Optimization problems often involve situations in which the user's goal is to minimize and/or maximize not a single objective function, but several, usually conflicting, functions simultaneously. Such ...

Abstract: Many complex problems encountered in both production and daily life can be conceptualized as combinatorial optimization problems (COPs). Many ad-hoc deep learning methods have been proposed ...

Heidi S. Enger ’27, an Associate Editorial Editor, is a Social Studies Concentrator in Eliot House. She’s enrolled in Ec10b this semester (don’t ask). Harvard students have to stop treating life like ...

ProcessOptimizer is a Python package designed to provide easy access to advanced machine learning techniques, specifically Bayesian optimization using, e.g., Gaussian processes. Aimed at ...

Abstract: A wide range of real applications can be modelled as the multiobjective traveling salesman problem (MOTSP), one of typical combinatorial optimization problems. Meta-heuristics can be used to ...

The problem of vibration control with artificial structures has been an important issue in aerospace [1,2], vehicle design [3], civil engineering [4], and vibration pollution [5]. The suppression, ...