ABSTRACT
This chapter describes direct search techniques found in the literature for solving various manufacturing optimization problems. Multistage decision problems can also be solved by the direct application of the classical optimization techniques. Most traditional optimization methods used for manufacturing applications can be divided into two broad classes: direct search methods requiring only the objective function values and gradient search methods requiring gradient information either exactly or numerically. Dynamic programming is a mathematical technique well suited for the optimization of multistage decision problems. Evolutionary optimization is a simple optimization technique developed by G.E.P. Box in 1957. Box's direct search method differs from these methods in that the algorithm works with a number of points instead of a single point. An algorithm starts with an initial point and depending on the transition rule used in the algorithm, a new point is determined. The algorithm, however, is simple to implement and has had success in solving many industrial optimization problems.
