Combinatorial optimization with AI is particularly important in the fields of artificial intelligence, automation, and Industry 4.0. It involves finding the best solution to a problem from a vast number of possible combinations. This sounds abstract, but it happens quite automatically in many everyday situations.<\/p>\n
A practical example: In a modern factory, orders, machines, and materials must be optimally coordinated. There are millions of ways to organise workflows, travel paths, or machine deployments. With conventional methods, it often takes too long to find the best combination. This is where Artificial Intelligence comes in: it can rapidly simulate millions of scenarios and propose the most efficient solution.<\/p>\n
Combinatorial optimisation with AI therefore means that computers help to optimally solve complex problems in the shortest possible time \u2013 and often much better than humans could alone. This allows resources to be saved, production times to be shortened, and costs to be reduced. For example, a delivery service becomes faster, a factory becomes more environmentally friendly, and a production process becomes more flexible.<\/p>","protected":false},"excerpt":{"rendered":"