Prof. L. Jeff Hong
Industrial and System Engineering
University of Minnesota
Talk:
Staffing under Taylor's Law: A Unifying Framework for Bridging Square-root and Linear Safety Rules
Abstract:
Staffing rules serve as an essential management tool in service industries to attain target service levels. Traditionally, the square-root safety rule, based on the Poisson arrival assumption, has been commonly used. However, empirical findings suggest that arrival processes often exhibit an “over-dispersion” phenomenon, in which the variance of the arrival exceeds the mean. In this paper, we develop a new doubly stochastic Poisson process model to capture a significant dispersion scaling law, known as Taylor's law, showing that the variance is a power function of the mean. We further examine how over-dispersion affects staffing, providing a closed-form staffing formula to ensure a desired service level. Interestingly, the additional staffing level beyond the nominal load is a power function of the nominal load, with the power exponent lying between 1/2 (the square-root safety rule) and 1 (the linear safety rule), depending on the degree of over-dispersion. Extensive numerical experiments with both simulated and real arrival data show that our proposed model and staffing rules significantly outperform various alternatives. This is a joint work with Weihuan Huang (Nanjing University), Jiheng Zhang (HKUST) and Xiaowei Zhang (HKUST).
Biography:
Jeff Hong is Professor in Department of Industrial and Systems Engineering at the University of Minnesota. Prior to joining the University, he held academic positions at the Hong Kong University of Science and Technology (2004-2014), City University of Hong Kong (2014-2018) and Fudan University (2018-2024). His research interests include stochastic simulation, stochastic optimization, statistical machine learning, and financial risk management. Prof. Hong is currently an associate editor of Management Science and ACM Transactions on Modeling and Computer Simulation. He was the Simulation Area Editor of Operations Research (2018-2023) and President of INFORMS Simulation Society (2020-2022).
