Abstract: Vehicle scheduling and dispatching are core optimization problems in large-scale vehicle fleet systems, directly influencing service efficiency, operating cost, and resource utilization.

Foundational optimization algorithms are the core driving force behind deep learning, evolving from early stochastic gradient descent (SGD) to the widely adopted Adam family. However, as the scale of ...

ABSTRACT: Mathematical optimization is a fundamental aspect of machine learning (ML). An ML task can be conceptualized as optimizing a specific objective using the training dataset to discern patterns ...

ABSTRACT: Mathematical optimization is a fundamental aspect of machine learning (ML). An ML task can be conceptualized as optimizing a specific objective using the training dataset to discern patterns ...

A new algorithm helps topology optimizers skip unnecessary iterations, making optimization and design faster, more stable and more useful. PROVIDENCE, R.I. [Brown University] — With the rise of 3D ...

Schug discusses the role of surrogate modelling in chromatographic method development and process optimization. Surrogate modelling is emerging as a powerful tool in chromatographic method development ...

In recent years, the use of prompts to guide the output of Large Language Models have increased dramatically. However, even the best of experts struggle to choose the correct words to stitch up a ...

Abstract: Optimization methods are crucial for enhancing the performance of 5G and 6G networks, particularly for beamforming and transmission power control, which ensures efficient spectrum ...