Dynamic optimization and optimal control problems form the backbone of numerous applications in engineering, economics and the natural sciences. These methodologies involve determining a time-varying ...

We develop a novel framework, the implicit hitting set approach, for solving a class of combinatorial optimization problems. The explicit hitting set problem is as follows: given a set U and a family ...

The rise of AI, graphic processing, combinatorial optimization and other data-intensive applications has resulted in data-processing bottlenecks, as ever greater amounts of data must be shuttled back ...

We investigate risk-averse stochastic optimization problems with a risk-shaping constraint in the form of a stochastic-order relation. Both univariate and multivariate orders are considered. We extend ...

Research teams from energy giant ExxonMobil and IBM have been working together to find quantum solutions to one of the most complex problems of our time: managing the tens of thousands of merchant ...

New research in quantum computing is moving science closer to being able to overcome supply-chain challenges and restore global security during future periods of unrest. The Russo-Ukrainian conflict ...

An optimization problem is one where you have to make the best decision (choose the best investments, minimize your company’s costs, find the class schedule with the fewest morning classes, or so on).

Rob De La Espriella is the creator of BlueDragon, a problem-solving system used by the US national laboratories and nuclear facilities. United States businesses are silently hemorrhaging trillions of ...