Bus Fleet Management Optimization Using the Augmented Weighted Tchebycheff Method

  • William Emiliano
  • Lino Costa
  • Maria do Sameiro Carvalho
  • José Telhada
Conference paper
Part of the Springer Proceedings in Mathematics & Statistics book series (PROMS, volume 223)


This paper presents a multi-objective optimization model for the buses fleet management problem. This model is solved using the Augmented Weighted Tchebycheff method. The aim is to minimize three objective functions, \(Z_1\) (CO\(_2\) emissions), \(Z_2\) (other types of emissions) and \(Z_3\) (total costs), for a bus fleet that uses four types of buses: diesel, electric bus, electric bus of fast charging, and Compressed Natural Gas (CNG). A public transport (PT) company of Joinville, Brazil, where it operates three different PT lines, owns the fleet. The respective data was modelled and optimized using the MS Excel solver. Results provided interesting insights concerning the most adequate strategy for bus selection according with public transport line characteristics and taking into account trade-off between costs and emissions. The results indicate that optimal solutions include the diesel in the Itinga line and the CNG in the South line. The electric bus is more adequate in the South-North line due to the large number of stops and low average speed. However, when the costs are disregarded, in some scenarios, the best option is the electric bus for all lines.


Augmented weighted tchebycheff Buses fleet management problem Ghg emissions 



This work has been supported by CNPq (National Counsel of Technological and Scientific Development, Brazil) and COMPETE: POCI-01-0145-FEDER-007043 and FCT - Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2013.


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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • William Emiliano
    • 1
  • Lino Costa
    • 1
  • Maria do Sameiro Carvalho
    • 1
  • José Telhada
    • 1
  1. 1.Algoritmi Research Center, Universidade do MinhoBragaPortugal

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