Profit-oriented shift scheduling of inbound contact centers with skills-based routing, impatient customers, and retrials

Abstract

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Abstract This paper presents a profit-oriented shift scheduling approach for inbound contact centers. The focus is on systems in which multiple agent classes with different qualifications serve multiple customer classes with different needs. We assume that customers are impatient, abandon if they have to wait, and that they may retry. A discrete-time modeling approach is used to capture the dynamics of the system due to time-dependent arrival rates. Staffing levels and shift schedules are simultaneously optimized over a set of different approximate realizations of the underlying stochastic processes to consider the randomness of the system. The numerical results indicate that the presented approach works best for medium-sized and large contact centers with skills-based routing of customers for which stochastic queueing models are rarely applicable. Terms of use: Documents in EconStor may

Using linear programming to analyze and optimize stochastic flow lines

“…For this reason we developed our discrete-time model which is presented in this paper. From a methodological point of view, our approach is very similar to the one presented by Helber and Henken (2007) for shift scheduling in contact centers.…”

Workforce planning incorporating skills: State of the art

“…When the skill class is undefined, such as in [15,49,55,66,76], the skill determinants are also undefined in the respective paper. However, in several cases, only the skill class is defined while the skill determinants are to be defined by the user [12,19,20,23,24,28,34,71,74,79,80,83,84,96,98,100,114].…”

“…While uncertainty is ubiquitous, it remains a very popular topic for the future research section of many papers. [7,54,58,69,71,76,86,88,98,99,104,105,107,113,120] Most papers that consider a stochastic problem account for the uncertainty in demand [7,54,58,69,71,76,86,88,98,99,104,107,113]. Furthermore, the required workload and required processing time for tasks can be stochastic as elaborated by Stratman et al [105] and Huang et al [76].…”

Dynamic capacitated lot sizing with random demand and dynamic safety stocks

“…Other applications of this sample average approximations can be found, e.g., in Bihlmaier et al (2009), Helber andHenken (2010). A general overview of scenario analysis methods is presented, e.g., in Mißler-Behr (1993).…”