Given a weighted graph @math and @math , a subgraph @math is a of @math if the lengths of shortest paths in @math are preserved in @math up to a multiplicative factor of @math . The problem aims to preserve distances in @math for only a subset of the vertices. We generalize the minimum-cost subsetwise spanner problem to one where vertices appear on multiple levels, which we call the (MLGS) problem, and describe two simple heuristics. Applications of this problem include road network building and multi-level graph visualization, especially where vertices may require different grades of service. We formulate a 0--1 integer linear program (ILP) of size @math for the more general minimum , which resolves an open question by Sigurd and Zachariasen on whether this problem admits a useful polynomial-size ILP. We extend this ILP formulation to the MLGS problem, and evaluate the heuristic and ILP performance on random graphs of up to 100 vertices and 500 edges.
Given a graph G, a subgraph G′ is a t-spanner of G, if for every u, v ∈ V, the distance from u to v in G′ is at most t times longer than the distance in G. In this paper we give a very simple algorithm for constructing sparse spanners for arbitrary weighted graphs. We then apply this algorithm to obtain specific results for planar graphs and Euclidean graphs. We discuss the optimality of our results and present several nearly matching lower bounds.