The DOE SC program in Advanced Scientific Computing Research (ASCR) hereby announces its interest in basic research in the design, development, analysis, and scalability of randomized algorithms for ...

Combinatorial optimisation algorithms are central to addressing problems in which the goal is to select an optimal solution from a finite set of alternatives. These algorithms have evolved ...

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 ...

Cambridge, UK, July 22, 2021 – In a development the company said “is likely to set a new industry standard,” scientists at Cambridge Quantum (CQ) have developed a new algorithm for solving ...

We present a probabilistic greedy search method for combinatorial optimisation problems. This approach is implemented and evaluated for the Set Covering Problem (SCP) and shown to yield a simple, ...

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

In a new development that is most likely to establish a new industry standard, scientists at Cambridge Quantum (CQ) have created a new algorithm for solving combinatorial optimization problems that ...

Many applications solve problems that are sequential decision processes: an algorithm is given an a priori distribution over scenarios from which an unknown scenario is chosen and the task is to ...

Graph algorithms and combinatorial optimisation form a pivotal area of research that underpins many modern computational applications. At their core, graph algorithms provide systematic methods for ...

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 ...