Case Details

The case is situated in the context of the Paratransit Service, initiated by a social welfare organization in Hong Kong to provide accessible transport for persons with disabilities. While the organization demonstrated strong performance in punctuality and service pledges, historical data revealed concerns that these targets may have been achieved at the expense of user needs. The case examines both the demand and supply dimensions of the service to identify potential discrepancies between operational efficiency and user satisfaction. Against this backdrop, the study illustrates the value of integrating modern data analytics techniques with combinatorial optimization frameworks in addressing complex vehicle routing problems. Specifically, the case demonstrates the application of Google’s open-source OR-Tools as a practical instrument for formulating and solving logistics challenges. In the process, learners engage with data preparation tasks, including cleaning and visualization, to diagnose operational inefficiencies and uncover latent service issues. This analytical foundation enables the construction of optimization models that explores routing efficiency. Through this integrated approach, the case equips learners with technical competence in optimization methods while fostering insight into the complexities of service delivery in urban environments.