Duchrau, Petra; Frischmuth, Kurt A numerical search algorithm for experimental design. (English) Zbl 0719.90058 Rostocker Math. Kolloq. 40, 83-94 (1990). Optimum experimental design is considered as a nonconvex optimization problem. Special properties of this class of problems are derived, two assertions express the meaning of the symmetry of the objective function together with local convexity. Further, the concept of SLM (semi-local minimizers) is introduced which provides a new algorithm. A convergence theorem for a special case based on actual analytic results on D-optimal designs is proved. The summarized outcome of some numerical experiments with several models of practical interest concludes the paper. Reviewer: K.Frischmuth MSC: 90C26 Nonconvex programming, global optimization 90C90 Applications of mathematical programming 62K05 Optimal statistical designs 90C30 Nonlinear programming 62P10 Applications of statistics to biology and medical sciences; meta analysis Keywords:numerical search algorithm; Optimum experimental design; nonconvex optimization; semi-local minimizers; D-optimal designs PDFBibTeX XMLCite \textit{P. Duchrau} and \textit{K. Frischmuth}, Rostocker Math. Kolloq. 40, 83--94 (1990; Zbl 0719.90058)