Bulanık Çok Yanıtlı Deneyler İçin Bulanık Pareto Çözüm Kümesinin Bulanık İlişkiye Dayalı Sınıflandırma Yaklaşımı İle Değerlendirilmesi

The solution set of a multi-response experiment is characterized by Pareto solution set. In this paper, the multi-response experiment is dealed in a fuzzy framework. The responses and model parameters are considered as triangular fuzzy numbers which indicate the uncertainty of the data set. Fuzzy least square approach and fuzzy modified NSGA-II (FNSGA-II) are used for modeling and optimization, respectively. The obtained fuzzy Pareto solution set is grouped by using fuzzy relational clustering approach. Therefore, it could be easier to choose the alternative solutions to make better decision. A fuzzy response valued real data set is used as an application.

Evaluation of Fuzzy Pareto Solution Set by Using Fuzzy Relation Based Clustering Approach For Fuzzy Multi-Response Experiments

The solution set of a multi-response experiment is characterized by Pareto solution set. In this paper, the multiresponse experiment is dealed in a fuzzy framework. The responses and model parameters are considered as triangular fuzzy numbers which indicate the uncertainty of the data set. Fuzzy least square approach and fuzzy modified NSGA-II (FNSGA-II) are used for modeling and optimization, respectively. The obtained fuzzy Pareto solution set is grouped by using fuzzy relational clustering approach. Therefore, it could be easier to choose the alternative solutions to make better decision. A fuzzy response valued real data set is used as an application.

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