in this paper a guided tabu search (gts) is utilized for optimal nodal ordering of finite element models (fems) leading to small profile for the stiffness matrices of the models. the search strategy is accelerated and a graph-theoretical approach is used as guidance. the method is evaluated by minimization of graph matrices pattern equivalent to stiffness matrices of finite element models. comp...

Graph convolutional networks (GCNs) have received significant attention from various research fields due to the excellent performance in learning graph representations. Although GCN performs well compared with other methods, it still faces challenges. Training a model for large-scale graphs conventional way requires high computation and storage costs. Therefore, motivated by an urgent need term...

This paper provides an insight into graph coloring application of the contemporary heuristic methods. It discusses a variety algorithmic solutions for The Graph Coloring Problem (GCP) and makes recommendations implementation. GCP is NP-hard problem, which aims at finding minimum number colors vertices in such way, that none two adjacent are marked with same color.With advent multicore processin...

Abstract We study the behavior of Lorentzian Engle-Pereira-Rovelli-Livine spinfoam amplitude with homogeneous boundary data, under a graph refinement going from five to twenty tetrahedra. This can be interpreted as wave function Universe, for which we compute geometrical operators, correlation functions, and entanglement entropy. The numerical calculation is made possible by adapting Metropolis...