Abstract This thesis investigates a class of direct search methods for system optimization where it is assumed that the dependent variable is a unimodal function of N independent variables. The best optimization procedure is that which requires the least number of evaluations of the dependent variable. It is assumed that either the function or its derivative is unknown. The basic form of the search techniques studied requires the establishment of (N + 1) test points in N dimensions. Three...