Coupling multiagent simulation and GIS: an application in waste management

Urban solid waste management is one of the most demanding issues of today's urban areas, requiring large investments for efficient daily collection. Decision makers in the field face many complex decisions varying from solid waste collection to strategy development for the entire urban solid waste management process. Although several researchers have proposed algorithmic solutions and optimization techniques, not a single approach can handle all the variations. We propose a model for dealing with the complexity of the field based on integration of GIS data and multiagent simulation into an intelligent decision support system. This paper demonstrates the model and our initial work towards developing the system. In general, the collection process is abstracted to an agent model, simulation scenarios are executed and results are validated against field data. Our approach provides substantial benefits for the decision makers in the field, enabling them to experiment with possible scenarios and optimize their decisions.