Evaluating the Impact of Intermediate Facilities on Waste Collection Operations

Abstract

Given the importance of improving municipal solid waste management, the Optimisation Group from the University of Pretoria completed preliminary studies on data obtained from waste collection vehicle global position system traces from the City of Cape Town and found that some waste vehicles spend more time travelling between service locations and dump-sites as opposed to collecting waste. In order to improve these operations it was proposed that intermediate facilities be used to reduce the travel distance. The purpose of this project is to identify potential locations for intermediate waste facilities (transfer stations) by using a location model and then evaluating the impact of the intermediate waste facilities on waste vehicle collection operations. This was achieved by splitting the project into three phases. Since some of the data that was required was not readily available, it had to be generated rst. In phase one that data sets were generated. In phase two a variant of the location modelling formulation known as the multi-facility location problem was solved using the generalised Weiszfeld method for the multi-facility location problem. Up to 25 potential intermediate facility locations were identi ed and used for the remaining phase. In the next phase two models were built in order to quantitatively evaluate the impact of said facilities on waste collection operations. The rst model was concerned with the travel distance and travel time for each collection vehicle associated to a single collection beat (service location). The second model was concerned with the waste allocation from the collection beats to either an intermediate facility or a land ll site and from the intermediate facilities to a land ll. The model was also used to conduct a cost bene t analysis. It was concluded that as the number of intermediate facilities increased, the travel distance, travel time as well as the total transportation cost of the system decreased. Additionally, the location of the two existing intermediate facilities in the City of Cape Town were ine cient when compared to the same number of intermediate facilities located with the Weiszfeld algorithm. Furthermore, it was identi ed that the optimal number of facilities to locate, in the City of Cape Town, in order to reap the cost savings from improving the existing intermediate facility locations with respect to the capital cost of building new facilities, was three.