In the era of big data and artificial intelligence, a new approach has emerged for solving combinatorial optimization ...

The traveling salesman problem is considered a prime example of a combinatorial optimization problem. Now a Berlin team led by theoretical physicist Prof. Dr. Jens Eisert of Freie Universität Berlin ...

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 ...

Integer programming and combinatorial optimization form the backbone of many decision-making and resource allocation problems across diverse fields, from logistics and telecommunications to finance ...

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 ...

In this graduate-level course, we will be covering advanced topics in combinatorial optimization. We will start with matchings and cover many results, extending the fundamental results of matchings, ...

Dr. James McCaffrey of Microsoft Research shows how to implement simulated annealing for the Traveling Salesman Problem (find the best ordering of a set of discrete items). The goal of a combinatorial ...

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.

Although computers are overwhelmingly digital today, there’s a good point to be made that analog computers are the more efficient approach for specific applications. The authors behind a recent paper ...

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 ...

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 ...