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While this is without doubt a complex exercise, control theory provides the very tools we require to handle this complexity tractably.
Bio-inspired techniques like self-organization are a key feature to handle this complexity.
To handle this complexity, the approach of Model Based Systems Engineering is applied in this contribution.
As a result, there is a need for efficient algorithms that can handle this complexity.
Model-Based Systems Engineering (MBSE) methods are one approach to handle this complexity.
Hence rational design frameworks that handle this complexity are required to make significant progress.
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The used delivery algorithm is capable of handling this complexity relying on simple local information.
Recently, many researchers have shifted the focus from traditional optimization methods to the use of meta-heuristic approaches for handling this complexity.
In order to help a business to generate sustainable business ideas handling this complexity in a systematic and comprehensive manner, this paper proposes a method to formulate a wide variety of causalities in our society into a cause effect pattern library and illustrates how to use it for design and planning of sustainable businesses.
An effort should be made to educate more skilled professionals to handle the complexity of this work.
Robots can handle the complexity of this increasingly intricate world, allowing our attention to focus on the humans around us rather than on screens, buttons and keys.
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