The term multi-objective optimisation is particularly important in the fields of Artificial Intelligence, Industry and Industry 4.0, as well as Sustainability and Environment 4.0. Here, multiple objectives often need to be achieved simultaneously – for example, in the development of new products, the deployment of machinery, or the planning of processes.
Simply put, multi-objective optimisation means considering several objectives at the same time and trying to meet them as well as possible. This is a challenge because these objectives often conflict with each other. A well-known example from industry: a company wants to manufacture a product as cheaply as possible (objective 1), while at the same time offering high quality (objective 2) and protecting the environment (objective 3).
Using modern methods, such as artificial intelligence, such goal conflicts can be better resolved. The software calculates many different possibilities and helps to find a good compromise between the objectives. This allows the company to save costs, as well as improve quality and sustainability.
In short, multi-objective optimisation ensures that the best possible and most balanced decision is made in complex situations with multiple goals.
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