Real-world optimization problems often require an external “modeling engine” that computes fitnesses or data that are then input to an objective function. These programs often have much longer ...

Abstract: This paper explores the optimization of the production process based on statistical sampling and integer linear programming. Initially, we designed a sampling inspection plan to help ...

Abstract: The ability to accurately estimate the road condition is critical for the safety and performance of Automated Driving (AD) systems. Deep learning models are commonly used for this purpose, ...

Multifidelity optimization can inform decision-making during process development and reduce the number of experiments ...