For years, quantum computing has lingered on the edges of industry conversation, fascinating but often dismissed as too ...

Not all productivity advice is built for deep thinkers. Some of the most praised habits may actually disrupt the kind of ...

Route optimization, contamination detection, protecting revenue streams, and predictive maintenance are not separate ...

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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 ...

Three Opinion writers break down the former vice president’s book of excuses. By Michelle Cottle Carlos Lozada and Lydia Polgreen Produced by Vishakha Darbha Three Opinion writers weigh in on Kamala ...

A general-purpose Model Context Protocol (MCP) server for solving combinatorial optimization problems with logical and numerical constraints. This server provides a unified interface to multiple ...

We present OPT-BENCH, a benchmark comprising 20 machine learning tasks and 10 NP problems, specifically designed to assess large language models’ (LLMs) ability to solve problems with large search ...

1 School of Mathematics and Statistics, Sichuan University of Science and Engineering, Zigong, China. 2 Institute of Computational Mathematics and Scientific/Engineering Computing, Chinese Academy of ...

Impact Statement: The multi-objective traveling salesman problem (MOTSP), one of the typical combinatorial optimization problems, can be used to model a broad range of real applications.

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 ...