Research Output

Using an evolutionary algorithm to discover low CO2 tours within a Travelling Salesman Problem

  This paper examines the issues surrounding the effects of using vehicle emissions as the fitness criteria when solving routing problems using evolutionary techniques. The case-study examined is that of the Travelling Salesman Problem (TSP) based upon the road network within the City of Edinburgh, Scotland. A low cost path finding algorithm (A*) is used to build paths through the street network between delivery points. The EA is used to discover tours that utilise paths with low emissions characteristics. Two methods of estimating CO2 emissions are examined; one that utilises a fuel consumption model and applies it to an estimated drive cycle and one that applies a simplistic CO2 calculation model that focuses on average speeds over street sections. The results of these two metrics are compared with each other and with results obtained using a
traditional distance metric.

  • Date:

    31 December 2010

  • Publication Status:


  • Publisher


  • DOI:


  • Library of Congress:

    QA75 Electronic computers. Computer science

  • Dewey Decimal Classification:

    388 Transportation; ground transportation


Urquhart, N. B., Scott, C., & Hart, E. (2010). Using an evolutionary algorithm to discover low CO2 tours within a Travelling Salesman Problem. In C. Chio, A. Brabazon, G. A. Di Caro, M. Ebner, M. Farooq, A. Fink, …N. Urquhart (Eds.), Applications of evolutionary computation : EvoApplications 2010: EvoCOMNET, EvoENVIRONMENT, EvoFIN, EvoMUSART, and EvoTRANSLOG, Istanbul, Turkey, April 7-9, 2010, Proceedings, Part II. , (421-430).




vehicle routing; Travelling Salesman; fuel consumption; CO2 emissions; path finding algorithm;

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