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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.
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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.
Model-Based Systems Engineering (MBSE) methods are one approach to handle this complexity.
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.
Hence rational design frameworks that handle this complexity are required to make significant progress.
One way to handle this complexity is by devising satisficing measures for the relevant uncertainties.
Hence, rational design frameworks that handle this complexity are required to move this field from labs to industrial practice.
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