Finding the trade-off between emissions and disturbance in an urban context

  • Jasmin Grabenschweiger
  • Fabien Tricoire
  • Karl F. Doerner
Article
  • 83 Downloads

Abstract

We introduce the bi-objective emissions disturbance traveling salesman problem (BEDTSP), which aims at minimizing carbon dioxide emissions (\(\hbox {CO}_2\)) as well as disturbance to urban neighborhoods, when planning the tour of a single vehicle delivering goods to customers. Although there exist recent studies on minimizing emissions, we are not aware of any work on minimizing disturbance. We develop four different mathematical models for the BEDTSP. We also develop several data generation strategies for minimizing disturbance. These strategies consider optional nodes, thus allowing detours that yield less disturbance but also possibly more emissions. All models and strategies are compared in an extensive computational study. Experimental results allow us to derive clear guidelines for which model and data generation strategy to use in which context. Following these guidelines, we conduct a case study for the city of Vienna.

Keywords

City logistics \(\hbox {CO}_2\) emissions Disturbance Bi-objective traveling salesman problem Bi-objective shortest path problem 

Notes

Acknowledgements

The present research has been conducted in the context of the Green City Hubs Project, #FA379051 funded by Austrian Research Promotion Agency (FFG). We want to thank Christoph Six from the Institute for Powertrains and Automotive Technology of the Technical University of Vienna and Andreas Krawinkler from our department for providing us with real-world data.

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Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  1. 1.Department of Business AdministrationUniversity of ViennaViennaAustria
  2. 2.Institute for Production and Logistics ManagementJohannes Kepler UniversityLinzAustria
  3. 3.Christian Doppler Laboratory for Efficient Intermodal Transport OperationsViennaAustria

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