John E. Hopcroft – författare

This IMA Volume in Mathematics and its Applications MODELING, MESH GENERATION, AND ADAPTIVE NUMERICAL METHODS FOR PARTIAL DIFFERENTIAL EQUATIONS is based on the proceedings of the 1993 IMA Summer Program "Modeling, Mesh Generation, and Adaptive Numerical Methods for Partial Differential Equations." We thank Ivo Babuska, Joseph E. Flaherty, William D. Hen- shaw, John E. Hopcroft, Joseph E. Oliger, and Tayfun Tezduyar for orga- nizing the workshop and editing the proceedings. We also take this oppor- tunity to thank those agencies whose financial support made the summer program possible: the National Science Foundation (NSF), the Army Re- search Office (ARO) the Department of Energy (DOE), the Minnesota Su- percomputer Institute (MSI), and the Army High Performance Computing Research Center (AHPCRC). A vner Friedman Willard Miller, Jr. xiii PREFACE Mesh generation is one of the most time consuming aspects of com- putational solutions of problems involving partial differential equations. It is, furthermore, no longer acceptable to compute solutions without proper verification that specified accuracy criteria are being satisfied.Mesh gen- eration must be related to the solution through computable estimates of discretization errors. Thus, an iterative process of alternate mesh and so- lution generation evolves in an adaptive manner with the end result that the solution is computed to prescribed specifications in an optimal, or at least efficient, manner. While mesh generation and adaptive strategies are becoming available, major computational challenges remain. One, in particular, involves moving boundaries and interfaces, such as free-surface flows and fluid-structure interactions.

This IMA Volume in Mathematics and its Applications MODELING, MESH GENERATION, AND ADAPTIVE NUMERICAL METHODS FOR PARTIAL DIFFERENTIAL EQUATIONS is based on the proceedings of the 1993 IMA Summer Program "Modeling, Mesh Generation, and Adaptive Numerical Methods for Partial Differential Equations." We thank Ivo Babuska, Joseph E. Flaherty, William D. Hen- shaw, John E. Hopcroft, Joseph E. Oliger, and Tayfun Tezduyar for orga- nizing the workshop and editing the proceedings. We also take this oppor- tunity to thank those agencies whose financial support made the summer program possible: the National Science Foundation (NSF), the Army Re- search Office (ARO) the Department of Energy (DOE), the Minnesota Su- percomputer Institute (MSI), and the Army High Performance Computing Research Center (AHPCRC). A vner Friedman Willard Miller, Jr. xiii PREFACE Mesh generation is one of the most time consuming aspects of com- putational solutions of problems involving partial differential equations. It is, furthermore, no longer acceptable to compute solutions without proper verification that specified accuracy criteria are being satisfied.Mesh gen- eration must be related to the solution through computable estimates of discretization errors. Thus, an iterative process of alternate mesh and so- lution generation evolves in an adaptive manner with the end result that the solution is computed to prescribed specifications in an optimal, or at least efficient, manner. While mesh generation and adaptive strategies are becoming available, major computational challenges remain. One, in particular, involves moving boundaries and interfaces, such as free-surface flows and fluid-structure interactions.

This book constitutes the refereed proceedings of the 8th International Frontiers of Algorithmics Workshop, FAW 2014, held in Zhangjiajie, China, in June 2014. They provide a focused forum on current trends of research on algorithms, discrete structures, operations research, combinatorial optimization and their applications.

This book constitutes the refereed proceedings of the Third International Frontiers of Algorithmics Workshop, FAW 2009, held in Hefei, Anhui, China, in June 2009. The 33 revised full papers presented together with the abstracts of 3 invited talks were carefully reviewed and selected from 87 submissions. The papers are organized in topical sections on graph algorithms; game theory with applications; graph theory, computational geometry; machine learning; parameterized algorithms, heuristics and analysis; approximation algorithms; as well as pattern recognition algorithms, large scale data mining.