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Hierarchical branch and bound algorithm for computational grids
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DOI：10.1016/j.future.2012.03.001.png)
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Abstract
En 中文
Branch and Bound (B&B) algorithms are efficiently used for exact resolution of combinatorial optimization problems (COPs). They are easy to parallelize using the Master/Worker paradigm (MW) but limited in scalability when solving large instances of COPs on large scale environments such as computational grids. Indeed, the master process rapidly becomes a bottleneck. In this paper, we propose a new approach H-B&B for parallel B&B based on a hierarchical MW paradigm in order to deal with the scalability issue of the traditional MW-based B&B. The hierarchy is built dynamically and evolves over time according to the dynamic acquisition of computing nodes. The inner nodes of the hierarchy (masters) perform branching operations to generate sub-trees and the leaves (workers) perform a complete exploration of these sub-trees. Therefore, in addition to the parallel exploration of sub-trees, a parallel branching is adopted. H-B&B is applied to the Flow-Shop scheduling problem. Unlike most existing grid-based B&B algorithms, H-B&B has been experimented on a real computational grid (Grid'5000). The results demonstrate the scalability and efficiency of H-B&B. (C) 2012 Elsevier B.V. All rights reserved.
Keywords:
Parallel branch and bound
Master/worker
Hierarchical master/worker
Grid computing
Large scale experiments
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IF:
6.1
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6.8K
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