Genetic Algorithms for Municipal Solid Waste Collection and Routing Optimization

  • Nikolaos V. Karadimas
  • Katerina Papatzelou
  • Vassili G. Loumos
Part of the IFIP The International Federation for Information Processing book series (IFIPAICT, volume 247)


In the present paper, the Genetic Algorithm (GA) is used for the identification of optimal routes in the case of Municipal Solid Waste (MSW) collection. The identification of a route for MSW collection trucks is critical since it has been estimated that, of the total amount of money spent for the collection, transportation, and disposal of solid waste, approximately 60–80% is spent on the collection phase. Therefore, a small percentage improvement in the collection operation can result to a significant saving in the overall cost. The proposed MSW management system is based on a geo-referenced spatial database supported by a geographic information system (GIS). The GIS takes into account all the required parameters for solid waste collection. These parameters include static and dynamic data, such as the positions of waste bins, the road network and its related traffic, as well as the population density in the area under study. In addition, waste collection schedules, truck capacities and their characteristics are also taken into consideration. Spatiotemporal statistical analysis is used to estimate inter-relations between dynamic factors, like network traffic changes in residential and commercial areas. The user, in the proposed system, is able to define or modify all of the required dynamic factors for the creation of alternative initial scenarios. The objective of the system is to identify the most cost-effective scenario for waste collection, to estimate its running cost and to simulate its application.


Genetic Algorithm Solid Waste Municipal Solid Waste Travel Salesman Problem Travel Salesman Problem 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© International Federation for Information Processing 2007

Authors and Affiliations

  • Nikolaos V. Karadimas
    • 1
  • Katerina Papatzelou
    • 1
  • Vassili G. Loumos
    • 1
  1. 1.School of Electrical and Computer Engineering, Multimedia Technology LaboratoryNational Technical University of AthensAthensGreece

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