  This extended abstract presents an overview on NP-hard optimization problems
with multiple interdependent components. These problems occur in many
real-world applications: industrial applications, engineering, and logistics.
The fact that these problems are composed of many sub-problems that are NP-hard
makes them even more challenging to solve using exact algorithms. This is
mainly due to the high complexity of this class of algorithms and the hardness
of the problems themselves. The main source of difficulty of these problems is
the presence of internal dependencies between sub-problems. This aspect of
interdependence of components is presented, and some outlines on solving
approaches are briefly introduced from a (meta)heuristics and evolutionary
computation perspective.
