Leveraging ML models to directly learn network flow configurations from empirical data can deliver robustly high performance, surpassing that of demand-prediction methods. To gain a deeper theoretical ...

1 Department of Mathematics, University of Patras, Patras, Greece. 2 Department of Business Administration, University of Patras, Patras, Greece. This paper presents a new dimension reduction strategy ...

In 2022, a team of computer scientists presented a groundbreaking algorithm for the maximum flow problem: How does one transport the most supplies from a source node to a sink node in a network while ...

In this paper, aiming to achieve the target of carbon emission orientation, a multi-objective optimization model of the multi-energy flow coupling system is proposed, in which all the environmental ...

Abstract: In this paper, we investigate the maximum flow routing strategy with the service function chain (SFC) constraints in the space information networks (SINs), where a SFC consists of a specific ...

Abstract: The maximum concurrent flow problem (MCFP) is a multicommodity flow problem in which every pair of vertices can send and receive flow concurrently. The objective of MCFP is to find a maximum ...

Quantum annealing algorithms belong to the class of metaheuristic tools, applicable for solving binary optimization problems. Hardware implementations of quantum annealing, such as the quantum ...