This study introduces a hybrid feature selection technique with a multi-objective algorithm incorporating Information Gain, Random Forest, and Relief F-based approach. We integrate the strengths of filter and wrapper methodologies to enhance the efficacy of addressing feature selection. The...

Within the Frequentist Model Averaging framework for linear models, we introduce a multi-objective model averaging methodology that extends both the generalized Jackknife Model Averaging (JMA) and the Mallows Model Averaging (MMA) criteria. Our approach constructs estimators based on stochastic...

Ultrasonic wire bonding, a highly automated production process, finds extensive use in the electronics and electromobility sectors, with billions of applications annually. Wire bonding, a critical step in electrical manufacturing, demands high quality while rising energy costs push industries to...

This study contributes to the advancement of supply chain scheduling (SCS) through the development of a comprehensive mathematical framework that unifies multi-objective supplier selection, demand allocation, production scheduling, and inventory management within flexible manufacturing systems...