Reprint

Symmetry in Graph Theory

Edited by
March 2019
340 pages
  • ISBN978-3-03897-658-5 (Paperback)
  • ISBN978-3-03897-659-2 (PDF)

This book is a reprint of the Special Issue Symmetry in Graph Theory that was published in

Biology & Life Sciences
Chemistry & Materials Science
Computer Science & Mathematics
Physical Sciences
Summary

This book contains the successful invited submissions to a Special Issue of Symmetry on the subject of “Graph Theory”.

Although symmetry has always played an important role in Graph Theory, in recent years, this role has increased significantly in several branches of this field, including but not limited to Gromov hyperbolic graphs, the metric dimension of graphs, domination theory, and topological indices. This Special Issue includes contributions addressing new results on these topics, both from a theoretical and an applied point of view.

Format
  • Paperback
License
© 2019 by the authors; CC BY-NC-ND license
Keywords
Metric dimension; basis; resolving set; gear graph; generalized gear graph; Devaney chaos; hypercyclicity; topological transitivity; topologically mixing; disjointness; connectivity; topological indices; cuprite; atom bond connectivity index; Zagreb indices; geometric arithmetic index; general Randić index; titanium difluoride; direct product of graphs; geodesics; Gromov hyperbolicity; bipartite graphs; alpha-boron nanotube; resolving set; metric basis; metric dimension; distinguishing number; functigraph; complete graph; graph operators; gromov hyperbolicity; geodesics; topological indices; general (α,t)-path sum-connectivity index; polycyclic aromatic hydrocarbons; resolving set; domination; secure resolving set and secure resolving domination; harmonic index; harmonic polynomial; inverse degree index; products of graphs; algorithm; general randić index; atom-bond connectivity (ABC) index; geometric-arithmetic (GA) index; Hex-Derived Cage networks; HDCN1(m,n), HDCN2(m,n); dominating set; binary locating-domination number; rotationally-symmetric convex polytopes; ILP models