Neural network (NN) has been tentatively combined into multi-objective genetic algorithms (MOGAs) to solve the optimization problems in physics. However, the computationally complex physical ...

Coverage optimization in wireless sensor networks (WSNs) is critical due to two key challenges: (1) high deployment costs arising from redundant sensor placement to compensate for blind zones, and (2) ...

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 ...

Computer-generated holography (CGH) provides an approach to digitally modulate a given wavefront. This technology, partly inherited from optical holography and partly advanced by the progress of ...

Optimization problems can be tricky, but they make the world work better. These kinds of questions, which strive for the best way of doing something, are absolutely everywhere. Your phone’s GPS ...

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 ...