Digital Library

of the European Council for Modelling and Simulation



Municipal Waste Collection Of Large Items Optimized With

ArcGis Network Analyst


Nikolaos V. Karadimas, Maria Kolokathi, Gerasimoula Defteraiou,

Vassili Loumos

Published in:


ECMS 2007 Proceedings

Edited by: Ivan Zelinka, Zuzana Oplatkova, Alessandra Orsoni


ISBN: 978-0-9553018-2-7

Doi: 10.7148/2007


21st European Conference on Modelling and Simulation,

Prague, June 4-6, 2007


Citation format:

Karadimas, N. V., Kolokathi, M., Defteraiou, G., & Loumos, V. (2007). Municipal Waste Collection Of Large Items Optimized With ArcGis Network Analyst. ECMS 2007 Proceedings edited by: I. Zelinka, Z. Oplatkova, A. Orsoni (pp. 80-85). European Council for Modeling and Simulation. doi:10.7148/2007-0080.



In the present paper the ArcGIS Network Analyst Algorithm is introduced for best routing identification applied in municipal waste collection of large items. The proposed application takes into account all the required parameters for the waste collection of large items so as its desktop users to be able to model realistic network conditions and scenarios. In this case, the simulation consists of scenarios of visiting loading spots in the municipality of Athens, in order to collect large items that couldn’t be collected by the standard waste collection trucks, due to size and other prohibitive obstacles. The Network Analyst is used to estimate interrelations between the dynamic factors, like network traffic changes (closed roads due to natural or technical causes, for example, fallen trees, car accidents, etc) in the area under study and to produce optimized solutions. The user is able to define or modify all the required dynamic factors for the creation of an initial scenario, and by modifying these particular parameters, alternative scenarios can be generated leading to several solutions. Finally, the optimal solution is identified by a function that takes into consideration various parameters, for example the shortest distance, road network as well as social and environmental implications.

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