The leading approach to the simplex method, a widely used technique for balancing complex logistical constraints, can’t get ...

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, ...

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 ...

Dani Gluck, PhD is Senior Algorithmics Researcher for LightSolver, conducting algorithm development and related mathematical and theoretical-physical research for the company’s proprietary Laser ...

Machine learning and deep learning have been widely embraced, and even more widely misunderstood. In this article, I’ll step back and explain both machine learning and deep learning in basic terms, ...