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 ...

Gone are the days of just blueprints, prototypes and calculations, as engineering now revolves around efficiency, speed and precision in a world where technology is rapidly changing. The world of ...

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 ...

The course is designed to provide engineering students a view of optimization as a tool for engineering decision making. Students will be given a fundamental introduction to the optimization ...

Genetic algorithms (GAs) mimic natural selection to solve complex optimization problems across engineering, AI, and science. By evolving a population of solutions through selection, crossover, and ...

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 ...

New integration and patterning schemes used in 3D memory and logic devices have created manufacturing and yield challenges. Industrial focus has shifted from the scaling of predictable unit processes ...

In the fast-evolving field of electronic systems design, engineers are under increasing pressure to deliver innovative, high-performance products within ever ...

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

Recent benchmark results show GPT-5.5 excels at coordinating tools for well-defined engineering tasks but still falters on extended, multi-step challenges. For civil and environmental engineers, ...