Étude de Problèmes d'Optimisation Combinatoire à Multiples Composantes Interdépendantes
This is an incremental overview for researchers and practitioners in industrial, engineering, and logistics applications.
The paper addresses NP-hard optimization problems with multiple interdependent components, which are challenging to solve due to high complexity and internal dependencies, and outlines solving approaches from a metaheuristics and evolutionary computation perspective.
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.