By leveraging inference-time scaling and a novel "reflection" mechanism, ALE-Agent solves the context-drift problems that ...

Combinatorial optimisation is a fundamental field in applied mathematics and computer science that focuses on finding an optimal object from a finite set of objects. In this context, problems are ...

Conventional quantum algorithms are not feasible for solving combinatorial optimization problems (COPs) with constraints in the operation time of quantum computers. To address this issue, researchers ...

MicroAlgo Inc. announced its research on the Quantum Information Recursive Optimization (QIRO) algorithm, which aims to address complex combinatorial optimization problems using quantum computing.

Bicycle sharing systems have become an attractive option to alleviate traffic in congested cities. However, rebalancing the number of bikes at each port as time passes is essential, and finding the ...

The rise of AI, graphic processing, combinatorial optimization and other data-intensive applications has resulted in ...

We might be witnessing the start of a new computing era where AI, cloud and quantum begin to converge in ways that redefine ...

Dr. James McCaffrey of Microsoft Research uses full code samples to detail an evolutionary algorithm technique that apparently hasn't been published before. The goal of a combinatorial optimization ...

The proposed algorithm combines variational scheduling with post-processing to achieve near-optimal solutions to combinatorial optimization problems with constraints within the operation time of ...

Traffic congestion has been worsening since the 1950s in large cities thanks to the exorbitant number of cars sold each year. Unfortunately, the figurative price tag attached to excessive traffic ...