Conventional quantum algorithms are not feasible for solving combinatorial optimization problems (COPs) with constraints in the operation time of quantum computers. To address this issue, researchers ...

A framework based on advanced AI techniques can solve complex, computationally intensive problems faster and in a more more scalable way than state-of-the-art methods, according to a new study. A ...

A line of engineering research seeks to develop computers that can tackle a class of challenges called combinatorial optimization problems. These are common in real-world applications such as ...

University of Tennessee researchers James Ostrowski and Rebekah Herrman are developing quantum-computing tools to tackle multi-stage stochastic decision problems in fields like energy, logistics, and ...

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 ...

Modern optimization theory, algorithms, and applications in process engineering. Topics include the fundamentals of linear programming, integer programming, nonlinear programming, mixed-integer ...