Numerous real-world applications involve large-scale multi-objective optimization problems (LSMOPs) with hundreds or even thousands of decision variables. Although multi-objective evolutionary ...

When designing new computer chips, engineers need to make various decisions about how to connect their underlying components ...

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 ...

The traveling salesman problem is considered a prime example of a combinatorial optimization problem. Now a Berlin team led by theoretical physicist Prof. Dr. Jens Eisert of Freie Universität Berlin ...

The whole supply chain of the world is basically suboptimal because we don't have the computing to run large-scale, efficient ...

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 ...

If your supply chain is drowning in variables, constraints and constant change, quantum optimization may offer a smarter way ...

Meta AI mathematics open problems got a new answer on October 2, 2026: six papers co-authored by mathematicians and Muse Spark in Thinking Mode via ordinary meta.ai chat -- five tackling previously ...

Neel Somani points out that while artificial intelligence may look like it runs on data and algorithms, its real engine is optimization. According to Somani, every breakthrough in the field—from ...

I had my self-made "evolutionary optimization engine" solve a problem for which the answer was already known.It automatically ...

You make decisions every day. Some are big, and some are small. But even the small decisions involve a great deal of complexity. Let me show you what I mean. Take something you probably do regularly: ...