A Fast Bandwidth Minimization Algorithm
We propose a simple and direct node shifting method with hill climbing for the well-known matrix bandwidth minimization problem. Many heuristics have been developed for this NP-complete problem including the Cuthill-McKee (CM) and the Gibbs, Poole and Stockmeyer (GPS) algorithms. Recently, heuristics such as Simulated Annealing, Tabu Search and GRASP have been used, where Tabu Search and the GRASP with Path Relinking achieved significantly better solution quality than the CM and GPS algorithms. Experimentation shows that our method achieves the best solution quality when compared with these while being much faster than newly-developed algorithms.
Sparse matrices, bandwidth, heuristics
Operations and Supply Chain Management
International Journal of Artificial Intelligence Tools
LIM, Andrew; RODRIGUES, Brian; and XIAO, Fei.
A Fast Bandwidth Minimization Algorithm. (2007). International Journal of Artificial Intelligence Tools. 16, (3), 537-544. Research Collection Lee Kong Chian School Of Business.
Available at: http://ink.library.smu.edu.sg/lkcsb_research/609