|M.Sc Student||Feldman Zohar|
|Subject||Optimal Staffing of Systems with Skills-Based-Routing|
|Department||Department of Industrial Engineering and Management||Supervisor||Professor Emeritus Avishai Mandelbaum|
|Full Thesis text|
In this work we optimize operational costs of systems with Skills-Based-Routing (SBR). In such systems, heterogeneous customers are routed to different types of servers, based on the servers’ skills. In the setting we consider, each server skill is associated with a corresponding cost, and service level can either appear as strong constraint or incur a cost.
This work is motivated mainly by Telephone Call Centers, where the term SBR is taken from. The SBR framework, however, arises in other context of service systems, for example technical support providers, banking systems, health-care etc.
The solution we propose is based on the Stochastic Approximation (SA) approach. Since SBR models are analytically intractable in general, we use computer simulation to evaluate service-level measures. Under the assumption of convexity of the service level functions in the staffing levels, SA provides an analytical proof of convergence, together with a rate of convergence. We show via numerical examples that, although the convexity assumption does not hold for all cases and all types of service-level objectives, the algorithm still succeeds in identifying the optimal solution. We also apply our algorithms within time-varying environments, in particular to a realistic Call Center.