论文标题
通过粒子群优化生成精确的最佳设计：通过案例研究评估功效和效率
Generating Exact Optimal Designs via Particle Swarm Optimization: Assessing Efficacy and Efficiency via Case Study
论文作者
论文摘要
在这项研究中，我们解决了文献中有关粒子群优化应用以生成最佳设计的应用的现有缺陷。我们介绍了一项大型计算机研究的结果，在该研究中，我们可以在PSO效率和功效，以生成高质量的候选设计，以针对工业从业人员通常遇到的小型外表面情景。展示并推荐了PSO的首选版本。此外，与流行的本地优化器（例如坐标交换）相反，PSO也证明，即使在一次运行中，也可以在小计算成本下生成具有较大概率的高效设计。因此，对于更多的从业者采用和使用PSO作为生成候选实验设计的工具似乎有益。
In this study we address existing deficiencies in the literature on applications of Particle Swarm Optimization to generate optimal designs. We present the results of a large computer study in which we bench-mark both efficiency and efficacy of PSO to generate high quality candidate designs for small-exact response surface scenarios commonly encountered by industrial practitioners. A preferred version of PSO is demonstrated and recommended. Further, in contrast to popular local optimizers such as the coordinate exchange, PSO is demonstrated to, even in a single run, generate highly efficient designs with large probability at small computing cost. Therefore, it appears beneficial for more practitioners to adopt and use PSO as tool for generating candidate experimental designs.
