Selection of real estate operations & maintenance (O&M) contractors using a multi-hybrid AI system

With the increasing activity of facilities management since several years we observe the multiplication of multi-technical contracts in real estate operations & maintenance (O&M) engineering. Selection of one or more contractors is actually rather complex and important financial and service quality challenges depend on it. The present paper proposes a method to predict contractors’ performances so as to select the one who can best respond to O&M demands. With this aim, a Neuro-Fuzzy System (NFS) associated with a hybrid and adaptive genetic algorithms (GAs) method has been developed. Important problems are considered – choice of hybridization or adaptation parameters, necessary data pre-processing,ldots The results of simulations concerning the client satisfaction levels for O&M will show the pertinence of such a data-pre-processing.

Bigaud David, Thibault François, Tregouet Pierre-Julien