Decision Trees and Multi-objective Optimization to Calibrate Process Parameters

The paper introduces an innovative approach to address the challenge of determining process parameter settings to achieve desired goals. We propose a mathematical programming approach that integrates a multi-objective formulation with decision tree models. These decision tree models predict different targets, and the mathematical model combines their outputs with other process requirements. A case study demonstrates the effectiveness of our model and compares its performance to a method based on a multi-objective decision tree. The results reveal that our method, employing multiple single-objective decision trees, outperforms the conventional approach utilizing a single multi-objective decision tree. The suggested outcomes provide the most suitable parameter ranges based on their target preferences.