Optimization over convex sets described as the intersections of the set of symmetric, positive semidefinite matrices with affine spaces. Formulations of problems from combinatorial optimization, graph ...

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 ...

The quantum approximate optimization algorithm (QAOA) has the potential to approximately solve complex combinatorial optimization problems in polynomial time. However, current noisy quantum devices ...

The talk focuses on expander graphs in conjunction with the combined use of SDPs and eigenvalue techniques for approximating optimal solutions to combinatorial optimization problems. In the first part ...

Solving Combinatorial Optimization Problem Over Graph Through QUBO Transformation and Deep Reinforcement Learning Abstract: Many complex problems encountered in both production and daily life can be ...

The quantum approximate optimization algorithm (QAOA) is one of the most promising candidates for achieving quantum advantage through quantum-enhanced combinatorial optimization. A near-optimal ...

Solving combinatorial optimization problems holds significant practical importance, and many such problems can be transformed into MILP problems. Currently, Branch-and-Bound (B&B) is a typical method ...

However, large-scale combinatorial optimization problems are very computationally intensive to solve using standard computers, making researchers turn to other approaches.