Amélioration multicritère d'options dans les systèmes complexes
Résumé
Designing the way a complex system should evolve to better match the customers' requirements provides an interesting class of applications for muticriteria evaluation and improvement. In this paper a complex system is characterized by its input parameters. Not all combinations of parameters lead to admissible systems for the customer since some requirements must usually be fulfilled. The company needs to construct a model of the preferences of the customer based on his decision criteria. Thus, the required models to support the improvement design of a complex system must include both preference models and system behavioral models. In our framework, a Multi Attributes Utility Theory model captures the decisions related to preferences in the design process whereas a fuzzy representation is proposed to model the relationships between systems parameters and performances to capture operational constraints. An algorithm based upon both models is proposed to compute a sequence of efficient action plans to improve the system.