Optimal solid waste collection routes identified by the ant colony system algorithm.

In the present paper, the Ant Colony System (ACS) algorithm is used for the identification of optimal routes in the case of municipal solid waste (MSW) collection. 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 the 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. Spatio-temporal 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. Finally, the results of the ACS algorithm are compared with the empirical method currently used by the Municipality of Athens.