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首页> 外文期刊>Applied Intelligence: The International Journal of Artificial Intelligence, Neural Networks, and Complex Problem-Solving Technologies >Boosting an evolution strategy with a preprocessing step: application to group scheduling problem in directional sensor networks
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Boosting an evolution strategy with a preprocessing step: application to group scheduling problem in directional sensor networks

机译:使用预处理步骤提升演化策略:应用于方向传感器网络中的组调度问题

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摘要

This paper presents a two-membered evolution strategy based approach to address the total rotation minimization problem (TRMP) pertaining to directional sensor networks. TRMP is an -hard problem. Performance of the proposed approach is enhanced by employing a pre-processing step that utilizes a constructive heuristic and the concept of opposite solutions. We have compared our approach with the best approach available in the literature. The experimental results demonstrate our approach to be highly effective with substantial gain in terms of solution quality, in comparison to the best approach available in the literature. However, our approach requires more time in comparison to this approach.
机译:本文介绍了基于两人的演化策略的方法,解决了与方向传感器网络有关的总旋转最小化问题(TRMP)。 TRMP是一个绝地问题。 通过采用利用建设性启发式和相反解决方案概念的预处理步骤,提高了所提出的方法的性能。 我们将我们的方法与文献中的最佳方法进行了比较。 实验结果表明,与文献中可用的最佳方法相比,我们在解决方案质量方面非常有效的方法。 然而,我们的方法与这种方法相比需要更多的时间。

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