Staffing multi-skill call centers via search methods and a performance approximation

Abstract

Abstract. We address a multi-skill staffing problem in a call center where the agent skill sets are exogenous and the call routing policy has well-specified features of overflow between different agent types. Constraints are imposed on the service level for each call class, defined here as the steady-state fraction of calls served within a given time threshold, where calls that abandon after having waited for service less than the threshold are excluded. We develop an approximation of these service levels, allowing an arbitrary overflow mechanism and allowing customer abandonment.We then develop a two-stage heuristic that finds good solutions to mathematical programs with such constraints. The first stage uses search methods supported by the approximation. Because service-level approximation errors may be substantial, we adjust the solution in a second stage in which performance is estimated by simulation. We solve realistic problems of varying size and routing policy. Our approach is shown to be competitive with (and often better than) previously available methods.

The Modern Call Center: A Multi‐Disciplinary Perspective on Operations Management Research

“…Similarly, Cezik and L'Ecuyer (2006) propose a methodology that combines linear programming with simulation to determine a schedule. Avramidis et al (2007) develop search methods that use queueing performance approximations to produce agent schedules for a multi-skill call center.…”

Optimization of Multi-skill Call Centers Contracts and Work-shifts

“…In addition it is also necessary to consider a significant number of constraints implied by the contracts (part-time/full-time, number of working days, lunch breaks...) that are not often taken into account in the literature. The scientific literature is rich of contributions on models of incoming calls (Channouf et al 2007) and consequent phenomena of waiting queues, abandoned calls and call transfers by statistics and simulation techniques (Avramidis et al 2009). Some approaches have been proposed to optimize call centers taking into account all the above mentioned features but they mainly work in two phases: first the optimal set of operators is defined and then the optimal schedule is computed for the given set of operators (Pot 2006, Pisacane et al 2006.…”

A three-stage approach for aircraft line maintenance personnel rostering using MIP, discrete event simulation and DEA

“…This method is common in call center applications, where the workload depends on the distributions of call arrivals and durations (e.g., Henderson (2004, 2008); Avramidis, Chan, Gendreau, L'Ecuyer, and Pisacane (2010); Avramidis, Chan, and L'Ecuyer (2009)). …”