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 ...

Abstract: LGP has been successfully applied to dynamic job shop scheduling (DJSS) to automatically evolve dispatching rules. Flow control operations are crucial in concisely describing complex ...

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 ...

Abstract: In recent years, the addition-min fuzzy relation inequalities have been adopted to describe the flow constraint in a P2P network system. Each solution of the inequalities represents a ...

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 ...

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 ...