dc.description.abstract | Respecting global petroleum price goes up, traffic volume has significantly grown and private cars become more popular than before in Taiwan. Therefore, carpool that enhances the car occupancy rate can not only relieve traffic congestion, but can also cheapen the travel cost and save energy. Introducing the carpool has a lot of advantages, but fairness would affect carpool members that join in the activity. As regards in Taiwan, carpool matching is manually performed by planning personnels with experience in current practice, without a systematic analysis. Such a manual approach is considered to be less efficient, and can possibly result in an inferior feasible solution. The carpool problems with the consideration of fairness were solved according to the frequency of being a driver in literatures, instead of the driving distances. Therefore, in this research, the travel distances in the carpool problem is considered for the long-term intercity commute trips to address the issue. Based on the system planner perspective, we develop a system-optimized matching model. The matching model is expected to be an effective tool for the planner to help solve carpool members matching.
We consider many-to-many OD matching focusing on fairness in the carpool problem. Additional constraints are set to comply with real operating requirements. Model is formulated as an integer multiple commodity network flow problem, which is characterized as NP-hard and cannot be optimally solved in a reasonable time for large-scale problems. Therefore, to efficiently solve large-scale problems occurring in real world, we develop a solution algorithm for the model, based on Lagrangian relaxation with subgradient methods. To evaluate the matching model and solution algorithm in practice, we perform a case study. A computerized random generator is designed to create different problem instances used for testing. The results show the model could be useful. Finally, conclusions and suggestions are given. | en_US |