This article is a review of optimization in relationship to experiments in four aspects. The first is the use of optimization for designing experiments to provide the maximum amount of insight and information on the phenomena being investigated. Second, the use of experiments to perform optimization is reviewed. Third, the use of techniques developed for experimental optimization in numerical optimization is discussed. These first three aspects of optimization in relationship to experiments are discussed with an emphasis on reducing the number of required experiments or analyses. Finally, the importance of experimental validation of optimization is presented. Applications from a variety of fields are provided for each of these aspects. This review article contains 119 references.