Please use this identifier to cite or link to this item:
|Title:||Systems modelling of municipal solid waste collection operations|
|Authors:||Wilson, Gordon Bruce|
|Advisor:||Baetz, Brian W.|
|Keywords:||Civil Engineering;Civil Engineering|
|Abstract:||<p>Curbside collection of municipal solid waste is an expensive and increasingly complex operation. Municipalities across North America have been expanding their waste collection fleets steadily over the past decade due to population growth, the introduction of new collection services such as curbside recycling, and a decline in the number of active landfill sites. Despite the increasing cost and complexity of municipal solid waste collection systems, many collection programs are designed and operated without a clear understanding of the parameters responsible for those costs or the relationships between those parameters. Existing models of municipal waste collection operations often deal only with average system performance, ignoring large variations in important parameters such as the quantity of waste set out for collection or the percentage of households participating in a collection program. This research develops two different analytic models of municipal solid waste collection that explicitly address the variability of municipal solid waste collection operations. The first model is based on probability theory and vehicle dynamics, while the second model is based on queuing theory. Despite different starting assumptions, both models provide similar results and both models agree well with Monte Carlo computer simulation results. Both models are easier to use than computer simulations of the waste collection process, can be applied to any municipal waste collection operation, and can be coded on spreadsheets. The potential utility of the developed models has been demonstrated by application to a number of practical municipal solid waste collection problems. The models are not used to optimize systems of collection vehicles in this research, although they are used to generate improved strategies for the specific problems presented. However, either of the two models could be further incorporated into large scale optimization models for complete waste management systems. The models are of interest primarily to solid waste management practitioners. It is anticipated that they would make use of the models both to design new collection systems and to improve existing collection operations. Application of the models to local design and operational problems should result in more efficient and less costly waste collection operations. Specifically, these models can be used to minimize the size of the collection fleet and the amount of time required to collect municipal solid wastes, resulting in lower capital and operating costs, lower fuel consumption, and reduced air emissions from collection vehicles.</p>|
|Appears in Collections:||Open Access Dissertations and Theses|
Items in MacSphere are protected by copyright, with all rights reserved, unless otherwise indicated.