A Generic Solver Based on Functional Parallelism for Solving Combinatorial Optimization Problems(Distributed Cooperation and Agents)

概要

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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.
社団法人電子情報通信学会の論文
2006-06-01