Article ID: | iaor2002106 |
Country: | United Kingdom |
Volume: | 31 |
Issue: | 3 |
Start Page Number: | 203 |
End Page Number: | 220 |
Publication Date: | Jan 2001 |
Journal: | International Journal of Physical Distribution & Logistics Management |
Authors: | Abdinnour-Helm Sue |
Keywords: | optimization: simulated annealing, heuristics, transportation: air |
Locating hub facilities is important in different types of transportation and communication networks. The p-Hub Median Problem (p-HMP) addresses a class of hub location problems in which all hubs are interconnected and each non-hub node is assigned to a single hub. The hubs are uncapacitated, and their number p is initially determined. Introduces an Artificial Intelligence (AI) heuristic called simulated annealing to solve the p-HMP. The results are compared against another AI heuristic, namely Tabu Search, and against two other non-AI heuristics. A real world data set of airline passenger flow in the USA, and randomly generated data sets are used for computational testing. The results confirm that AI heuristic approaches to the p-HMP outperform non-AI heuristic approaches on solution quality.