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Contribution to Book
Greedy Trees, Caterpillars, and Wiener-Type Graph Invariants
Mathematical Chemistry Monographs: Distance in Molecular Graphs Theory
  • Nina S. Schmuck, Technische Universitat Graz
  • Stephen G. Wagner, Stellenbosch University
  • Hua Wang, Georgia Southern University
Document Type
Contribution to Book
Publication Date
1-1-2012
ISBN
978-86-6009-012-8
Disciplines
Abstract

The extremal questions of maximizing or minimizing various distance-based graph invariants among trees with a given degree sequence have been vigorously studied. In many cases, the so-called greedy tree and the caterpillar are found to be extremal. In this note, we show a “universal property” of the greedy tree with a given degree sequence, namely that the number of pairs of vertices whose distance is at most k is maximized by the greedy tree for all k. This rather strong assertion immediately implies, and is equivalent to, the minimality of the greedy trees with respect to graph invariants of the form Wf (T)= ∑ {u,v}⊆V (T) f(d(u, v)) for any nonnegative, nondecreasing function f. With different choices of f, one directly solves the minimization problems of distance-based graph invariants including the classical Wiener index, the Hyper-Wiener index and the generalized Wiener index. We also consider the maximization of some of such invariants among trees with a given degree sequence. These problems turned out to be more complicated. Analogous to the known case of the Wiener index, we show that Wf (T) is maximized by a caterpillar for any increasing and convex function f. This result also leads to a partial characterization of the structure of the extremal caterpillars. Through a similar approach, the maximization problem of the terminal Wiener index is also addressed.

Citation Information
Nina S. Schmuck, Stephen G. Wagner and Hua Wang. "Greedy Trees, Caterpillars, and Wiener-Type Graph Invariants" Mathematical Chemistry Monographs: Distance in Molecular Graphs Theory Vol. 12 (2012) p. 195 - 214
Available at: http://works.bepress.com/hua_wang/67/