Efficient Computing Budget Allocation for Finding Simplest Good Designs.
Efficient Computing Budget Allocation for Finding Simplest Good Designs.
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高效的计算预算分配，寻找最简单的良好设计
DOI：
10.1080/0740817x.2012.705454
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发表时间：
2013-01-01
期刊：
影响因子：
--
通讯作者：
Chen CH
中科院分区：
文献类型：
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作者：
Jia QS;Zhou E;Chen CH
在许多应用中，有些设计更容易实现，需要更少的训练数据和更短的训练时间，并且比其他设计消耗更少的存储。这种设计被称为简单设计，当它们都具有良好的性能时，通常优于复杂设计。尽管在基于仿真的优化中如何找到好的设计已经有了大量的研究，但在寻找最简单的好设计方面的研究却很少。本文认为这一重要问题，并作出了以下贡献的主题。首先，下界提供的概率正确地选择m个最简单的设计与最佳性能和选择最好的m个这样的最简单的好的设计，分别。其次，两个有效的计算预算分配方法，分别找到m个最简单的好的设计，并找到最好的m个这样的设计，并已证明其渐近最优性。第三，这两种方法的性能进行了比较，平均分配超过六个学术的例子和一个烟雾探测问题的无线传感器网络。
In many applications some designs are easier to implement, require less training data and shorter training time, and consume less storage than others. Such designs are called simple designs and are usually preferred over complex ones when they all have good performance. Despite the abundant existing studies on how to find good designs in simulation-based optimization, there exist few studies on finding simplest good designs. This article considers this important problem and the following contributions are made to the subject. First, lower bounds are provided for the probabilities of correctly selecting the m simplest designs with top performance and selecting the best m such simplest good designs, respectively. Second, two efficient computing budget allocation methods are developed to find m simplest good designs and to find the best m such designs, respectively, and their asymptotic optimalities have been shown. Third, the performance of the two methods is compared with equal allocations over six academic examples and a smoke detection problem in a wireless sensor network.