This book presents an intelligent, integrated, problem-independent method for multiresponse process optimization. In contrast to traditional approaches, the idea of this method is to provide a unique model for the optimization of various processes, without imposition of assumptions relating to the type of process, the type and number of process parameters and responses, or interdependences among them. The presented method for experimental design of processes with multiple correlated responses is composed of three modules: an expert system that selects the experimental plan based on the orthogonal arrays; the factor effects approach, which performs processing of experimental data based on Taguchias quality loss function and multivariate statistical methods; and process modeling and optimization based on artificial neural networks and metaheuristic optimization algorithms. The implementation is demonstrated using four case studies relating to high-tech industries and advanced, non-conventional processes.But, the other mentioned algorithms cannot be tested yet in the current Matlab environment (or in some other computing environment that ... This may be overcome by the development and usage of the problem-specific codes for the observed algorithms in Matlab. However ... Sadhana 30:699a711 Aladag CH, KApksoy O (2011) A tabu search meta-heuristic approach to the dual response systems problem.
|Title||:||Advanced Multiresponse Process Optimisation|
|Author||:||Tatjana V. Sibalija, Vidosav D. Majstorović|
|Publisher||:||Springer - 2015-07-25|