In this study, a simulation model was constructed and used to examine staff scheduling with particular attention to customer wait times at the cash register at a retail store. All operations performed by clerks were carefully examined to determine staff scheduling at the retail store on campus at Nagoya University. All required data for staffing problems were collected, including the point of sales (POS) data and time study data for all clerks, with reference to the company manuals.
Recently, operations at the convenience store have been overly complicated. There are 170 types of operations for clerks in the store, and the operations are defined by the manual for the convenience store, which is divided into 10 classes. To properly identify problem areas and solutions, various data points would need to be collected from the store.
This paper discusses a simulation IP-personnel planning, especially by making use of POS data. First, during the past two years, POS data was carefully reviewed to analyze the frequency with which customers came into the store. Thereafter, based on the correlation coefficients of the data, several customer frequency patterns were established. Then, a stepwise procedure for personnel scheduling was proposed. Simulation modeling was used together with integer programming to minimize total personnel expenses.
In this study, the work load for all operations in every time period is examined in terms of man-hour; hence, work loading is performed in relation to time elapsed during each 24-hour period during the first stage. Then, integer programming is adopted to obtain an initial feasible solution to staffing problems. Finally, simulation experiments are performed together with OptQuest, and optimal solutions are obtained.
A simulation modeling procedure for a retail store was proposed to determine the optimal number of clerks taking into account operation types, operation frequency, and staff scheduling. The procedure was designed to determine the optimal number of the clerks as necessary given the frequency of the operations involved.
In the procedure, work loading was performed during each 24-hour period in the first stage. Then, integer programming was used to obtain an initial feasible solution. Then, simulation experiments were performed together with OptQuest, and optimal solutions were obtained. The initial solution was obtained by solving the integer programming problem, and wait time was evaluated by performing the simulation. The proposed procedure was used for the actual case. It has been shown that staffing problems can be solved easily and effectively in a real-life situation.