This IMA Volume in Mathematics and its Appllcations GRAPH THEORY AND SPARSE MATRIX COMPUTATION is based on the proceedings of a workshop that was an integraI part of the 1991- 92 IMA program on "Applied Linear AIgebra." The purpose of the workshop was to bring together people who work in sparse matrix computation with those who conduct research in applied graph theory and grl: l, ph algorithms, in order to foster active cross-fertilization. We are grateful to Richard Brualdi, George Cybenko, Alan Geo ge, Gene Golub, Mitchell Luskin, and Paul Van Dooren for planning and implementing the year-Iong program. We espeeially thank Alan George, John R. Gilbert, and Joseph W.H. Liu for organizing this workshop and editing the proceedings. The finaneial support of the National Science Foundation made the workshop possible. A vner Friedman Willard Miller. Jr. PREFACE When reality is modeled by computation, linear algebra is often the con nec tiori between the continuous physical world and the finite algorithmic one. Usually, the more detailed the model, the bigger the matrix, the better the answer. Efficiency demands that every possible advantage be exploited: sparse structure, advanced com puter architectures, efficient algorithms. Therefore sparse matrix computation knits together threads from linear algebra, parallei computing, data struetures, geometry, and both numerieal and discrete algorithms."

This volume presents papers from the 2nd Scandinavian Workshop on Algorithm Theory. The contributions describe original research on algorithms and data structures, in all areas, including combinatorics, computational geometry, parallel computing, and graph theory. The majority of the papers focus on the design and complexity analysis of: data structures, text algorithms, and sequential and parallel algorithms for graph problems and for geometric problems. Examples of tech- niques presented include: - efficient ways to find approximation algorithms for the maximum independent set problem and for graph coloring; - exact estimation of the expected search cost for skip lists; - construction of canonical representations of partial 2-trees and partial 3-trees in linear time; - efficient triangulation of planar point sets and convex polygons.