Abstract
This paper proposes a new class of parallel branch-and-bound (B&B) schemes. The main idea of the scheme is to focus on the functional parallelism instead of conventional data parallelism, and to support such a heterogeneous and irregular parallelism by using a collection of autonomous agents distributed over the network. After examining several implementation issues, we describe a detail of the prototype system implemented over eight PC’s connected by a network. The result of experiments conducted over the prototype system indicates that the proposed parallel processing scheme significantly improves the performance of the underlying B&B scheme by adaptively switching exploring policies adopted by each agent participating to the problem solving.
This research was partially supported by the Grant-in-Aid for Scientific Research.
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Tagashira, S., Mito, M., Fujita, S. (2008). Towards Generic Solver of Combinatorial Optimization Problems with Autonomous Agents in P2P Networks. In: Labarta, J., Joe, K., Sato, T. (eds) High-Performance Computing. ISHPC ALPS 2005 2006. Lecture Notes in Computer Science, vol 4759. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77704-5_13
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DOI: https://doi.org/10.1007/978-3-540-77704-5_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-77703-8
Online ISBN: 978-3-540-77704-5
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