A STRATEGY BASED ON STATISTICAL MODELLING AND MULTI-OBJECTIVE OPTIMIZATION TO DESIGN A DISHWASHER CLEANING CYCLE

Date

2023-12-22

Author

ANAPA, KORKUT

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This thesis 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. First, regression models are built that are 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. The obtained optimization problem is then solved using evolutionary algorithms according to the designer's preferences (or customers' needs).

Subject Keywords

Dishwasher Design, Feature Selection, Multi-Objective Optimization, Evolutionary Algorithms, Statistical Modelling

URI

https://hdl.handle.net/11511/107595

Collections

Graduate School of Applied Mathematics, Thesis