Optimization Problems in Factorial and Response Adaptive Designs

实验设计是一个计划研究或调查有效方法以收集科学探究数据的过程。它是一种常用的工具，在科学研究中的应用，在工业，农业，生物，制药和制造科学等由于实验成本的增加，有一个迫切需要良好的设计，提高效率的参数估计和统计功率的结果测试。 最佳实验设计以最小的成本提供可解释和准确的推断。优化设计中的问题包括选择适当的最优性准则或几个准则的混合，以及通过分析或数值方法确定实际设计。优化设计中的挑战的特点是方法和计算问题，这为开发新的优化准则，优化设计理论，方法和算法搜索最优设计提供了机会。

Experimental design is a process of planning a study or investigating efficient methods for collecting data for scientific inquiry. It is a commonly used tool in scientific investigations with applications in industrial, agricultural, biological, pharmaceutical, and manufacturing sciences, etc. Due to the increasing cost of experiments, there is an urgent need for good designs that increase the efficiency of parameter estimation and the statistical power of the resulting tests. An optimal experimental design provides interpretable and accurate inference at minimal cost. Problems in optimal design include the selection of an appropriate optimality criterion or a mixture of several criteria and the determination of actual design, either analytically or numerically. The challenges in optimal design are characterized by methodological and computational issues, which provide opportunities for developing new optimality criteria, optimal design theory, methodology, and algorithms for searching for optimal designs.