| dc.description.abstract | To reduce the occurrence and fatality rate of drunk driving incidents, the government encourages the use of designated driving services. As the demand for such services rapidly increases, it becomes crucial for service providers to cope with the growing demand efficiently. Currently, designated drivers travel to the service starting points or leave from the service endpoints using public transportation, shared vehicles, or foldable electric vehicles. However, this operating mode may not be able to meet the future high demand for designated driving services. In view of this, this study considers the personal safety of customers and classifies them based on whether they request drivers of a specific gender from the perspective of designated driving companies. The objective is to minimize the total system cost by constructing a designated driving scheduling model, aiming to assist decision-makers in efficiently scheduling operations and assigning drivers and vehicles.
This study utilizes time-space network flow techniques to construct the designated driving scheduling model, and the model is solved directly using the C++ programming language in combination with the mathematical programming software CPLEX. To evaluate the practicality of the model, the study conducts example tests using randomly generated data and analyzes sensitivity and scenarios by adjusting different parameters and task demand scales. The results demonstrate that the model effectively utilizes resources and yields excellent outcomes when applied in practical settings. | en_US |