A strategy based on statistical modelling and multi-objective optimization to design a dishwasher cleaning cycle

Anapa K., YÜCEL H.

Expert Systems with Applications, cilt.249, 2024 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 249
  • Basım Tarihi: 2024
  • Doi Numarası: 10.1016/j.eswa.2024.123703
  • Dergi Adı: Expert Systems with Applications
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Anahtar Kelimeler: Dishwasher design, Evolutionary algorithms, Feature selection, Multi-objective optimization, Statistical modelling
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

This study proposes a novel approach based on statistical learning and multi-objective optimization to reduce the need for experiments during the design phase of new cleaning cycles for household dishwashers. We first build regression models associated with the feature selection methods to predict the outputs of a dishwasher cleaning cycle by using the existing cleaning cycles’ program flows as input data and the results of the performance laboratory tests of the related cleaning cycles as output data. Then, a multi-objective optimization problem is defined by assigning the regression models and chosen features as objective functions and unknown decision variables, respectively. Obtained optimization problem is then solved by using evolutionary algorithms according to the designer's preferences (or customers’ needs).