11h00 - 11h25
Staffing Optimization with Chance Constraints in Call Centers
We consider a problem of staffing call centers with respect to chance constraints. We introduce chance-constrained formulations of the scheduling problem which requires that the quality of service (QoS) constraints are met with high probability. We define a sample average approximation of this problem in a multi skill setting. We prove the convergence of the optimal solution of the sample-average problem to that of the original problem when the sample size increases. For the special case where we consider the staffing problem and all agents have all skills (a single group of agents), we design three simulation-based optimization methods for the sample problem. For the call center models in our numerical experiment, these algorithms give good solutions, i.e., most constraints are satisfied, and we cannot decrease any agent in any period to obtain better results. One advantage of these algorithms, compared with other methods, that they are very easy to implement.
11h25 - 11h50
Dynamic Call Routing Policies Using Call Waiting Times and Agent Idle Times
We propose new routing policies for multi-skill call centers where the matching priorities between calls and agents are defined as affine combinations of the customer waiting times and agent idle times. The quality of service constraints are formulated as penalty cost functions. Our policies are more flexible than traditional ones found in practice, and numerical examples show they also perform better in many situations.
11h50 - 12h15
Scheduling of Agents from Forecasted Future Call Arrivals at Hydro-Quebec’s Call Centers
In this project, we want to help the call center managers at Hydro-Québec (HQ) achieve a high quality service at low operating costs. Their current techniques of determining the schedules of their large-size workforce (1000+ employees) can be optimized. Our method will use mathematical model and simulation to consider complex union regulations and to reproduce the various activities that occur in a call center. We will test our algorithms based on real-life data provided by HQ.
12h15 - 12h40
Staffing Hydro-Québec Call Center: Modeling and Experiments
The presentation addresses the staffing problem of a multi-skills call center, taking into account the available resources. There is a lack of staff allocation methods designed to treat transient call-center simulation. That’s why we have developed two approaches denoted CCHQ and NomadCC in order to determine the required staffing per time step as small as 15 minutes throughout the day. CCHQ is based on a new original heuristic, while NomadCC is based on black-box optimization algorithm (Nomad). The two proposed approaches were tested on a set of data provided by the Hydro-Québec call center. CCHQ is the approach that gives the best results, it allows a significant reduction of required personnel while improving quality of service and in all cases we have experienced.