Operational planning of public transit with economic and environmental goals: application to the Minneapolis–St. Paul bus system

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.

[1]  Jing-Quan Li,et al.  Sustainability provisions in the bus-scheduling problem , 2009 .

[2]  Michael Forbes,et al.  An exact algorithm for multiple depot bus scheduling , 1994 .

[3]  Mansour Rahimi,et al.  JOINTLY OPTIMIZING COST, SERVICE, AND ENVIRONMENTAL PERFORMANCE IN DEMAND-RESPONSIVE TRANSIT SCHEDULING , 2003 .

[4]  Mate Barany,et al.  Solving vehicle assignment problems by process-network synthesis to minimize cost and environmental impact of transportation , 2011 .

[5]  Albert P. M. Wagelmans,et al.  Models and Algorithms for Single-Depot Vehicle Scheduling , 2001, Transp. Sci..

[6]  M. Carrion,et al.  A computationally efficient mixed-integer linear formulation for the thermal unit commitment problem , 2006, IEEE Transactions on Power Systems.

[7]  Luis F. Miranda-Moreno,et al.  Eco-driving training and fuel consumption: Impact, heterogeneity and sustainability , 2017 .

[8]  Natalia Kliewer,et al.  An overview on vehicle scheduling models , 2009, Public Transp..

[9]  L. Bodin.  ROUTING AND SCHEDULING OF VEHICLES AND CREWS–THE STATE OF THE ART , 1983 .

[10]  Nigel N Clark,et al.  Factors Affecting Heavy-Duty Diesel Vehicle Emissions , 2002, Journal of the Air & Waste Management Association.

[11]  Hadi Dowlatabadi,et al.  Minimizing the health and climate impacts of emissions from heavy-duty public transportation bus fleets through operational optimization. , 2013, Environmental science & technology.

[12]  José M. P. Paixão,et al.  Vehicle Scheduling Problem with Multiple Type of Vehicles and a Single Depot , 1995 .

[13]  Gilbert Laporte,et al.  The bi-objective Pollution-Routing Problem , 2014, Eur. J. Oper. Res..

[14]  Avishai Ceder,et al.  Public-transport vehicle scheduling with multi vehicle type , 2011 .

[15]  C. Johansson,et al.  Source contributions to PM10 and arsenic concentrations in Central Chile using positive matrix factorization , 2005 .

[16]  Matthias Ehrgott,et al.  A discussion of scalarization techniques for multiple objective integer programming , 2006, Ann. Oper. Res..

[17]  Omar J. Ibarra-Rojas,et al.  Planning, operation, and control of bus transport systems: A literature review , 2015 .

[18]  Denis Borenstein,et al.  Review of real-time vehicle schedule recovery methods in transportation services , 2014, J. Sched..

[19]  B. Moor,et al.  Mixed integer programming for multi-vehicle path planning , 2001, 2001 European Control Conference (ECC).

[20]  Yong Geng,et al.  Co-benefit evaluation for urban public transportation sector – a case of Shenyang, China , 2013 .

[21]  Mohamadreza Banihashemi,et al.  Optimization Model for Large-Scale Bus Transit Scheduling Problems , 2000 .

[22]  Walter Ukovich,et al.  A comparison of different solution approaches to the vehicle scheduling problem in a practical case , 2000, Comput. Oper. Res..

[23]  Miguel A. Figliozzi,et al.  Vehicle Routing Problem for Emissions Minimization , 2010 .

[24]  Victor Parada,et al.  Reducing the carbon footprint in a vehicle routing problem by pooling resources from different companies , 2016 .

[25]  Saad Mekhilef,et al.  A review on global fuel economy standards, labels and technologies in the transportation sector , 2011 .

[26]  Samuel J. Raff,et al.  Routing and scheduling of vehicles and crews : The state of the art , 1983, Comput. Oper. Res..

[27]  Bixuan Sun,et al.  A Multi-Period, Multiple Objective, Mixed Integer Programming, GAMS Model for Transit System Planning , 2019 .

[28]  Qing-Shan Jia,et al.  Energy-Efficient Buildings Facilitated by Microgrid , 2010, IEEE Transactions on Smart Grid.

[29]  Gilbert Laporte,et al.  The Pollution-Routing Problem , 2011 .