Integrated Genetic Algorithm with Hill Climbing for the Bandwidth Minimization Porblem

• Main Authors: LIM, Andrew, RODRIGUES, Brian, XIAO, Fei
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2003
• Subjects: Operations and Supply Chain Management
• Online Access: https://ink.library.smu.edu.sg/lkcsb_research/2068; https://doi.org/10.1007/3-540-45110-2_41
• Institution: Singapore Management University

In this paper, we propose an integrated Genetic Algorithm with Hill Climbing to solve the matrix bandwidth minimization problem, which is to reduce bandwidth by permuting rows and columns resulting in the nonzero elements residing in a band as close as possible to the diagonal. Experiments show that this approach achieves the best solution quality when compared with the GPS [1] algorithm, Tabu Search [3], and the GRASP with Path Relinking methods [4], while being faster than the latter two newly-developed heuristics.