两种任务分配算法的性能比较

Anup Kumar, S. Ramakrishnan, Chinar Deshpande, L. Dunning
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引用次数: 7

摘要

本文研究了一种求解最优任务分配问题的新算法。分配基于Stone的“吞吐量”指标,其中最优性标准是执行和进程间通信的总成本。研究了两种解决相同问题的方法,一种是基于遗传算法的新方法,另一种是著名的树搜索算法a *。我们使用算法执行时间作为两种算法的性能标准。研究表明,对于较大的搜索空间,遗传算法比A*更有利,而对于较小的搜索空间,A*更有利。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Performance Comparison of Two Algorithms for Task Assignment
In this article we investigate a new algorithm for solving the optimal task assignment problem. The assignment is based on Stone's "throughput" metric with the optimality criteria being the total cost for execution and interprocess communication. Two approaches studied are a new approach based on genetic algorithms and A*, a well known tree search algorithm for solving the same problem. We use the algorithm execution time as a performance criteria for the two algorithms. It is shown that the genetic algorithm techniques are more favorable than A* for larger search spaces while for smaller search spaces A* is preferred.
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