We provide a method for deriving robust solutions to certain stochastic optimization problems, based on mean-covariance information about the distributions underlying the uncertain vector of returns.

Formulation and solution of applicable optimization models, including linear, integer, nonlinear, and network problems. Efficient algorithmic methods and use of oomputer modeling languages and systems ...

This paper investigates the effects of manufacturing variations in fuel injectors on the engine performance with emphasis on emissions. The variations are taken into consideration within a Reliability ...

Third, authors review Jupiter global mapping trajectories. Unlike the low-inclination tour trajectories, Jupiter’s global mapping trajectories need high inclinations. On the one hand, gravity assists ...

Scientists have developed a new optimization approach that combines both day-ahead optimization and real-time optimization to improve operations of PV-driven EV charging stations. The framework is ...

A group of researchers from New York’s Cornell University has developed a new building energy management method that combines quantum computing with model predictive control (MPC) to achieve energy ...

Latent AI and Wind River have announced a technical cooperation to integrate AI inference capabilities with real-time operating systems for edge computing applications. The partnership combines Wind ...