This study develops a framework to optimize bus assignments and operating practices to routes considering both operating costs and environmental goals. The mixed-integer programming model is applied to the Metro Transit bus system in the Minneapolis–St. Paul metropolitan area. The model is used to derive representative solutions on the efficient frontiers between operating costs and emissions, and to demonstrate how economic factors such as fuel cost and service level affect the trade-offs between costs and environmental outcomes. An analysis of fleet composition shows that vehicle assignments can significantly affect the cost and emission performance of the fleet. We then use the model to evaluate the actual bus assignment schedule used by Metro Transit, and provide suggestions on how to reduce operating costs and emissions. The model is useful in supporting strategic decisions such as vehicle replacement and purchase, as well as operational planning.
Bibliographical noteFunding Information:
This work is part of the project “Enabling the Next Generation of Super Hybrid Transit Bus”, which was jointly funded by the Initiative for Renewable Energy and the Environment (Grant number RL-0013-13) and the Center for Transportation Studies, both at University of Minnesota, and Metro Transit—the public transportation operator in the Minneapolis–St. Paul Metropolitan Area. We would like to thank Janet Hopper, David Haas and Chuck Wurzinger at Metro Transit for providing extensive datasets. We are also very grateful for the advice and assistance from Steven Taff, William Northrop, David Kittelson, Win Watts, Andrew Kotz, Shashank Singh and Kieran McCabe at the University of Minnesota, and the anonymous reviewers.
© 2019, Springer-Verlag GmbH Germany, part of Springer Nature.
- Environmental impacts
- Mixed-integer programming
- Multi-criteria optimization
- Operating costs
- Operational planning