ABSTRACT
Research in optimal experimental design has a long history and dates back as early as 1918 in a seminal paper by Smith (1918) and probably earlier. This chapter discusses algorithms for finding an optimal design given a statistical model defined on a given design space. We discuss background and the need for algorithms to find an optimal design for various situations. There are different types of algorithms available in the literature, and even for the same design problem, the researcher usually has several algorithms to choose from to find an optimal design. There are also algorithms that use specialized methods to find an optimal design for a very specific application. For example, Syed et al. (2011) used a mathematical programming technique to search for a D-optimal design using cyclotomic cosets. The literature on algorithms to find an optimal design for a statistical model is therefore huge and diverse.
