Abstract:
I shall describe a data-based modelling framework that supports analysis and optimization of large and complex, resource-scarce service-operations (e.g. hospitals, contact-centers, courts, banks). Guided by many-server asymptotic regimes, and drawing from Harrison’s Stochastic Processing Networks (SPNs), all participants in the service process (e.g. customers, servers) are equally considered resources that are either busy or await each others’ availability. Models are then activity-oriented, where each activity (e.g. service in a hospital) first consumes a subset of the resources at specific states (e.g. waiting patient, available doctor, idle exam-room); and then, upon completion, produces possibly other resources at other states (e.g. served patient, available doctor, exam-room that requires cleaning). We hence refer to our models as Resource-Driven Activity Networks, or RANs for short.

Ultimately and hopefully, RANs will enable the creation of models directly from data – automatically and in real-time; this will yield, among other things, theoretical guarantees (common OR practice) and actionable comparisons between plans vs. actual performance. A supporting research agenda has been advanced, for over 15 years, at the Technion SEE Laboratory (SEE = Service Enterprise Engineering). SEELab data will hence be used to make the agenda concrete and to motivate the RAN framework. SEELab experience also provides an opportunity (as time permits) to briefly comment on “OR/OM/IE Research – Quo Vadis?”

Joint work with Mor Armony, Nitzan Carmeli, Junfei Huang, Petar Momcilovic, Galit Yom-Tov.