Geospatial Modeling for Optimization of Solid Waste Disposal in a Rapidly Urbanizing City, Sari, in Iran

Solid waste management is an important component in the environmental system, and plays a key role in population health. Furthermore, Municipal Solid Waste Management (MSWM) is one of the critical environmental management challenges which is being faced by many developing countries including Iran due to a rapid urban development. The aim of this dissertation research was developing models of solid waste management. The developed models were integrated into a Geospatial technology to select landfill sites based on fuzzy logic tools in GIS and artificial neural network analysis by means of weekly quantity prediction data of solid waste. In this regard, the response surface model was applied to optimize the cost of collection and transportation of solid waste. In this study, extra parameters such as fuel consumption, machinery, and labor force (waste collection and transport) were applied for prediction of solid waste in order to assess their effect in improving the structure of ANN model and the training performance of generated model. To select the landfill site, three methods were applied known as additive weighting, ordered weighted averaging, and weighted linear combination. These methods were applied in a Fuzzy logic manner. According to the obtained results, there were many locations detected by OWA but not all of them were qualified. A Response Surface Model (RSM) was also implemented with conventional optimization techniques of solid waste management. The effects of three parameters such as fuel consumption, total labor, and volume of transport were also investigated. Later on, reasonable and simple expressions for calculating the influential factors were suggested and established out based on distribution of influential factors. The recommendations of this thesis consist of an implementation of a new solid waste management program which is suitable for recent urbanized area.

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