Özdemir, Akın2025-01-212025-01-2120191308-5514https://dergipark.org.tr/tr/download/article-file/765836https://dergipark.org.tr/tr/pub/umagd/issue/43865/497045https://doi.org/10.29137/umagd.497045https://hdl.handle.net/20.500.12587/19237Computer-aidedoptimal experimental designs are an effective quality improvement tool thatprovides insights of information under various quality engineering problems. Inthe literature, considerable attention has been focused on maximizing thedeterminant of the information matrix in order to generate optimal designpoints. However, minimizing the average prediction based on the I-optimality criterion is more usefulthan commonly used D-optimalitycriterion for a number of situations. In this paper, special experimentaldesign situations are explored where both qualitative and quantitative inputvariables are considered for an irregular design space with the pre-specifiednumber of design points and the first-order polynomial model. In addition, thispaper lays out the algorithmic foundations for the proposed D- and I-optimality criteria embedded mixed integer linear programmingmodels in order to obtain optimal operating conditions using the first-orderresponse functions. Comparative studies are also conducted. Finally, theproposed models are superior to the traditional counterparts.eninfo:eu-repo/semantics/openAccessQuality by designcomputer-aided designoptimum operating conditionmixed integer linear programmingoptimizationArticle12-55155910.29137/umagd.497045497045