Abstract

Service operations are often characterized as a seemingly endless series of waiting lines and servers. Almost every interaction between a consumer and the organization providing the service involves waiting in a queue. Capacity management is one response to the cry for a service performance improvement during the past decade. It represents the ability to balance demand and the capability of the service delivery system to satisfy the demand. A review of the literature reveals that an integrated approach of management strategies (demand and resources) is desirable. A feasible set of management policies to handle multi-tandem queuing systems characterized by stochastic demand is presented in this paper. This type of system is common in many high customer contact (HCC) service related organizations. An extensive study of the city of Montreal driver licensing office (Henri Bourrassa Complex) was conducted and explored. A GPSS/H based simulation model was developed and employed to manipulate various policy variables (demand management, labor assignment and job flexibility) in an effort to provide options for increased system efficiency. The use of simulation analysis permits the incorporation of complex system characteristics, therefore providing a realistic representation of the effects of possible management actions. Customer arrival patterns during a three week period in January and July were compared using this model. Using a full-factorial design and given the statistical analysis, it was evident that a deterministic customer arrival rates produce significantly shorter mean system transit times. The results also revealed that job flexibility policy as well as the moving server model have been the most effective in decreasing the customer waiting time in the system and reducing servers idle time