We developed Hierarchical Ant Colony Optimization (H-ACO) for solving railway rolling stock planning. H-ACO uses several colonies and allocates them hierarchically. However, it requires a huge amount of computation time for calculation using large number of colonies. In this paper, we implement H-ACO in parallel computation environment with multi-core processor in order to reduce its computation time. The effectiveness of the proposed method is demonstrated through a numerical experiment.
|Translated title of the contribution||Implementation of Hierarchical Ant Colony Optimization on Multi-core Parallel Computer and Its Performance Evaluation|
|Number of pages||5|
|Journal||IEICE technical report|
|Publication status||Published - Jan 21 2014|