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. © Springer-Verlag Berlin Heidelberg 2008.
CITATION STYLE
Tagashira, S., Mito, M., & Fujita, S. (2008). Towards generic solver of combinatorial optimization problems with autonomous agents in P2P networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4759 LNCS, pp. 152–163). Springer Verlag. https://doi.org/10.1007/978-3-540-77704-5_13
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