Traditional VR instruction often places students directly into immersive experiences without preparation, resulting in a cognitive “cold start”. To resolve this issue, the first step in the ...

My graduate studies included learning about constraint-based optimization algorithms (such as linear programming) and ...

Leaders run the risk of losing their strategic edge by blindly pushing AI for the sake of AI. Companies can no longer win the ...

Solving optimization problems is challenging for existing digital computers and even for future quantum hardware. The practical importance of diverse problems, from healthcare to financial ...

Abstract: A wide range of real applications can be modelled as the multiobjective traveling salesman problem (MOTSP), one of typical combinatorial optimization problems. Meta-heuristics can be used to ...

1 School of Mathematics and Statistics, Fuzhou University, Fuzhou, China. 2 College of Computer and Data Science, Fuzhou University, Fuzhou, China. In this paper, we use Physics-Informed Neural ...

Change is the only constant in today’s rapidly evolving digital marketing landscape. Keeping up with the latest innovations isn’t just a choice – it’s a necessity for survival. Generative engine ...

The paper presents a topology optimization methodology for 2D elastodynamic problems using the boundary element method (BEM). The topological derivative is derived based on the variation method and ...

Abstract: Ising machines are next-generation computers expected to efficiently sample near-optimal solutions of combinatorial optimization problems. Combinatorial optimization problems are modeled as ...