Modeling Municipal Solid Waste Collection Systems Using Derived Probability Distributions. I: Model Development

Abstract

This paper presents a derived probability model that can be used to estimate vehicle and labor requirements for municipal solid waste collection systems. The model consists of closed-form solutions for important performance parameters such as the mean and variance of the total collection time for a route of given size. The results of the model agree well with the results of Monte Carlo–simulation models of curbside collection, but the derived probability model has several advantages over simulation techniques. The analytical nature of the model allows it to be easily and directly implemented on a spreadsheet. The proposed model will allow solid waste managers to examine a wide range of collection alternatives without the time and expense of simulation modeling.