Optimizing Operator's and Users' Objectives in Non-Emergency Patients Transportation

Abstract

In this work, we study a Non-emergency Patients Transportation (NEPT) problem in the context of delivering such services in Hong Kong. The purpose of our work is to examine the user inconvenience (waiting time) with the goals of optimizing the vehicle utilization and operating costs. We developed a Mixed Integer Linear Programming (MILP) formulation for the NEPT problem and solved the mathematical model by CPLEX to get optimal results. Using a weighted objective function-based sensitivity analysis, the behaviour of the MILP model is analyzed regarding multiple performance measures, namely operating cost, underutilization level, and user waiting time. This study provides decision makers with the insights into the impacts of objective weights on different performance measures. Our solutions not only reduce the operating costs but also the patient inconvenience. Moreover, our computational experiments based on a case study demonstrate the effective implementation of the model and show the practicality of our methodology.