Information processing models generating lognormally distributed reaction times
Journal of Mathematical Psychology
Advances in evolutionary computing
Commissioned Paper: Telephone Call Centers: Tutorial, Review, and Research Prospects
Manufacturing & Service Operations Management
Optimizing Change Request Scheduling in IT Service Management
SCC '08 Proceedings of the 2008 IEEE International Conference on Services Computing - Volume 1
A simulation based scheduling model for call centers with uncertain arrival rates
Proceedings of the 40th Conference on Winter Simulation
Staffing Multiskill Call Centers via Linear Programming and Simulation
Management Science
Business-impact analysis and simulation of critical incidents in IT service management
IM'09 Proceedings of the 11th IFIP/IEEE international conference on Symposium on Integrated Network Management
Proceedings of the Winter Simulation Conference
A method for assessing influence relationships among KPIs of service systems
ICSOC'12 Proceedings of the 10th international conference on Service-Oriented Computing
Planning in the large: efficient generation of IT change plans on large infrastructures
Proceedings of the 8th International Conference on Network and Service Management
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Enterprises and service providers are increasingly challenged with improving the quality of service delivery while containing the cost. However, it is often difficult to effectively manage the conflicting needs associated with dynamic customer workload, strict service level constraints, and service personnel with diverse skill sets. In this paper we propose an optimization model to provide recommended staffing levels in a complex service delivery system. The optimization model minimizes the total staffing related variable cost while considering the contractual service level constraints, the skills required to respond to different types of service requests, and the shift schedules that the service agents must follow. We describe how model-based decision making can be conducted using a combination of optimization and discrete event simulation techniques. We demonstrate the applicability of the proposed approach in a large IT services delivery environment.