Optimization models and management strategies for service operations
Pengfei Zhang, 0000-0003-2599-717X · 2021
In this dissertation, we investigate operational issues and strategies for three different service systems. In the first essay, we study how decentralized customer flows of the shared mobility service lead to the imbalance between the vehicle supply and customer demand, as well as intervention strategies for the network provider to improve the system. In the second essay, we study the appointment scheduling problem for integrated practice units using a two-stage integer stochastic programming model. In the third essay, we first study a data-free and distribution-free statistical characterization of random variables and then utilize it to design the order statistic uncertainty set for robust optimization that can be used to deal with uncertainty in service operations. We demonstrate our approach on the portfolio selection problem and the results demonstrate that our approach has superior performance relative to other uncertainty sets. In short, the studies in this dissertation address core issues in service operations, e.g., matching supply with demand and dealing with uncertainty. We provide both managerial insights and new optimization decision-making models that can be applied to improve service operations.