Implementing SELC (sequential elimination of level combinations) for practitioners
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Genetic algorithms (GAs) are a popular technology to search for an optimum in a large search space. Wu, Mao and Ma prosposed the sequential elimination of levels (SEL) method to find an optimal setting. Using the new ideas of a forbidden array and weighted mutation, Mandal, Wu and Johnson used elements of both SEL and GAs to introduce a new global optimization technique called sequential elimination of level combinations (SELC) to find optima more quickly. SELC has direct applications in pharmaceutical industries and hence, it is of importance to write statistical software to implement SELC automatically. In this thesis, we have implemented SELC in SAS, Matlab and R.