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A Generic Solver Based on Functional Parallelism for Solving Combinatorial Optimization Problems Shigeaki TAGASHIRA Masaya MITO Satoshi FUJITA Publication IEICE TRANSACTIONS on Information and Systems Vol.E89-D No.6 pp.1940-1947 Publication Date: 2006/06/01 Online ISSN: 1745-1361 DOI: 10.1093/ietisy/e89-d.6.1940 Print ISSN: 0916-8532 Type of Manuscript: PAPER Category: Distributed Cooperation and Agents Keyword: combinatorial optimization problem, autonomous agents, parallel branch-and-bound, winner determination problem, Full Text: PDF(918.3KB)>>
Summary: 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. | ||||||||||
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