This paper addresses carrier aircraft landing scheduling considering bolting and aerial refueling. It defines fuel and wake ...

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

Research team debuts the first deterministic streaming algorithms for non-monotone submodular maximization, delivering superior approximation ratios with minimal memory and real-time throughput on ...

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

The quantum sector is shifting from speculative science to a commercial race, with hardware, software, and investment pipelines all accelerating at once. Instead of distant promises, companies and ...

Abstract: The variational quantum eigensolver (VQE) is an algorithm for finding the ground states of a given Hamiltonian. Its application to binary-formulated combinatorial optimization (CO) has been ...

This repository contains code relating to the paper "A Combinatorial Branch-and-Bound Algorithm for the Capacitated Facility Location Problem under Strict Customer Preferences" by Christina Büsing, ...

Want your business to show up in Google’s AI-driven results? The same principles that help you rank in Google Search still matter – but AI introduces new dimensions of context, reputation, and ...

古典最適化器を用いることなく、任意の次数のバイナリ組合せ最適化問題を解く量子アルゴリズム SamBa-GQWの提案。グラフとして表現される解空間における連続時間量子ウォークをベースとし ...

A new technical paper titled “Analog optical computer for AI inference and combinatorial optimization” was published by researchers at Microsoft Research, Barclays and University of Cambridge.

Abstract: Combinatorial optimization is a promising area for achieving quantum speedup. The quantum approximate optimization algorithm (QAOA) is designed to search for low-energy states of the Ising ...