Multiobjective optimization of transit bus fleets with alternative fuel options: The case of Joinville, Brazil

Abstract

This paper presents a multiobjective optimization model to find efficient bus fleet combinations taking into account greenhouse gas emissions, conventional air pollutant emissions and costs. The goal is to minimize, simultaneously, three objective functions, Z1 (CO2 emissions), Z2 (Other Types of Emissions), and Z3 (total costs), for a buses fleet of a transit agency. For this case, there were four types of buses (diesel, electric bus, electric bus of fast charging, and CNG (compressed natural gas bus), which were analyzed in three different lines (South-North, Itinga, and South-Central) in Joinville city, Brazil. The respective data were modeled and optimized using MS Excel. Two different scalarization methods (the Weighted Tchebycheff and the Augmented Weighted Tchebycheff) are used for solving this buses fleet management problem. Different tradeoffs, in terms of the objectives, were obtained. The choice of a bus type is directly related to the characteristics (number of stops, average speed among others) of each line. The electrical bus is the best choice for reducing emissions but has a high initial cost and low autonomy. The results indicate that in the South–North line due to the large number of stops and low average speed, the electric bus is the type of dominant. In the other lines, the dominant ones were the diesel bus in the Itinga line and the CNG bus in the South line.