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Designing a Universal Suboptimal Tree Integration Algorithm

机译:设计通用的次优树集成算法

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Processing hierarchical data structures, due to their increasing popularity, becomes more and more important. In our previous works we have developed many exact integration algorithms for trees, but designing a new algorithm for each new integration aim is resource consuming. In this paper we propose a universal integration method based on genetic programming heuristic. Experimental evaluation shows that this approach is slightly slower than exact algorithms and sometimes provides worse solutions. One important advantage however is that it may be applied with no additional effort to any problem, without the need for a long design phase.
机译:由于分层数据结构的日益普及,处理分层数据结构变得越来越重要。在我们以前的工作中,我们已经开发了许多精确的树木集成算法,但是为每个新的集成目标设计新的算法都会消耗资源。在本文中,我们提出了一种基于遗传程序启发式的通用集成方法。实验评估表明,这种方法比精确算法要慢一些,有时会提供更差的解决方案。但是,一个重要的优点是,无需花费很长时间的设计阶段,便可以将其应用于任何问题,而无需付出额外的努力。

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