Mesh-Partitioning with the Multiple Ant-Colony Algorithm

ed Abstract We present two heuristic mesh-partitioning methods, both of which build on the multiple ant-colony algorithm in order to improve the quality of the mesh partitions. The first method augments the multiple ant-colony algorithm with a multilevel paradigm, whereas the second uses the multiple ant-colony algorithm as a refinement to the initial partition obtained by vector quantization. The two methods are experimentally compared with the well-known mesh-partitioning programs. The Multiple Ant-Colony Algorithm: The main idea of the multiple antcolony algorithm (MACA) for k-way partitioning was recently proposed in [6, 7] and based on the metaheuristics developed by Dorigo et al. [3]. There are k colonies of ants that are competing for food, which in this case represents the vertices of the graph (the elements of the mesh). Eventually, ants gather food to their nests, i.e., they partition the mesh into k submeshes. Multilevel Algorithm m-MACA. An effective way to speed up and glo...

• Type: Conference
• Year: 2004
• Where: ANTSW
• Authors: Peter Korosec, Jurij Silc, Borut Robic
• Keywords: ANTSW 2004, Artificial Intelligence, Multilevel, Multilevel Algorithm M-MACA, Multiple Ant-colony Algorithm