CADULA—a graph-based model for monitoring CAD-processes
WG '89 Proceedings of the fifteenth international workshop on Graph-theoretic concepts in computer science
Algebraic solution for geometry from dimensional constraints
SMA '91 Proceedings of the first ACM symposium on Solid modeling foundations and CAD/CAM applications
Some examples of the use of distances as coordinates for Euclidean geometry
Journal of Symbolic Computation
Graph-based approach for solving geometric constraint problems
Graph-based approach for solving geometric constraint problems
A graph-constructive approach to solving systems of geometric constraints
ACM Transactions on Graphics (TOG)
Handbook of discrete and computational geometry
Geometric Constraint Solving and Applications
Geometric Constraint Solving and Applications
IEEE Transactions on Visualization and Computer Graphics
A Tutorial and Bibliographical Survey on Graph Grammars
Proceedings of the International Workshop on Graph-Grammars and Their Application to Computer Science and Biology
Use Graph Grammars to Design CAD-Systems!
Proceedings of the 4th International Workshop on Graph-Grammars and Their Application to Computer Science
EDM - A Data Model for Electronic CAD/CAM-Applications
WG '86 Proceedings of the International Workshop on Graphtheoretic Concepts in Computer Science
Clique is hard to approximate within n1-
FOCS '96 Proceedings of the 37th Annual Symposium on Foundations of Computer Science
| Hi-index | 0.00 |
A central issue in dealing with geometric constraint systems that arise in Computer Aided Design and Assembly is the generation of an optimal decomposition recombination plan that is the foundation of an efficient solution of the constraint system. For the first time, in this paper, we formalize, motivate and explain the optimal decomposition-recombination (DR) planning problem as a problem of finding a sequence of graph transformations Ti that maximizes an objective function subject to a certain criteria. We also give several performance measures phrased as graph transformation properties by which DR-planning algorithms can be analyzed and compared. Using these perfomance measures and formulation of the problem we develop a new DR-planner which represents a significant improvement over existing algorithms.