Optimization seeks to find the best. It could be to design a process that minimizes capital or maximizes material conversion, to choose operating conditions that maximize throughput or minimize waste, ...

The challenge of resource allocation for UAV swarms in dynamic and uncertain electromagnetic environments has been ...

My graduate studies included learning about constraint-based optimization algorithms (such as linear programming) and ...

The system's ability to learn and adapt from operational data resulted in continuous performance improvements over time. Hospital administrators reported significant reductions in scheduling conflicts ...

As renewable power rapidly reshapes global electricity systems, engineers face a growing challenge: how to operate increasingly complex grids with ...

By fusing behavioral data, real-time analytics and generative AI, the industry is entering a new era: attention hacking at ...

This course examines formulation and solution of applicable optimization models, including linear, integer, nonlinear, and network problems, efficient algorithm methods, and use of computer modeling ...

Dr. James McCaffrey of Microsoft Research says that when quantum computing becomes generally available, evolutionary algorithms for training huge neural networks could become a very important and ...

A team of computer scientists has come up with a dramatically faster algorithm for one of the oldest problems in computer science: maximum flow. The problem asks how much material can flow through a ...