Quantum annealing (QA) is a cutting-edge algorithm that leverages the unique properties of quantum computing to tackle complex combinatorial optimization problems (a class of mathematical problems ...

We present a novel multi-objective optimization algorithm, Archived Multi-Objective Simulated Annealing (AMOSA), based on simulated annealing for transient electromagnetic (TEM) one-dimensional ...

Combinatorial optimization underpins applications in artificial intelligence, logistics, and network design, yet classical techniques such as greedy search and dynamic programming struggle to balance ...

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 ...

In computer science, normally we care about asymptotic speedup: We care about, “What is your running time as a function of the size of the problem? Does it grow linearly? Does it grow quadratically?” ...

If you want to simulate a tic-tac-toe game, that’s easy. You can evaluate every possible move in a reasonable amount of time. Simulating antennas, however, is much harder. [Rosrislav] has been ...

The benchmark tests show that the noise-free realization of QA can significantly outperform state-of-the-art classical algorithms. Quantum annealing (QA) is a cutting-edge algorithm that leverages the ...