Geography Reference
In-Depth Information
Karadimas et al. (2007) employed the ant colony system algorithm for
monitoring, simulating, testing, and optimizing costs for different scenarios of
solid waste management systems. A GIS tool supported the municipal solid
waste management system by using parameters such as waste bin locations,
road network topology, and population density. Further research is required to
test the proposed model on an extended area. Apaydin and Gonullu (2007)
published results of their research in route optimization for solid waste
collection in the city of Trabzon, Turkey. The city of Trabzon is as large as the
city of Kragujevac, Serbia and has 185,000 inhabitants. For 39 districts in the
city, a shortest path model was used in order to optimize solid waste collection
and hauling processes, as minimum cost was aimed. The Route View ProTM
software as an optimization tool was used for that purpose and the success was
around 4-59% for distance and 14-65% for time. The total benefit was 24% in
total costs or about 18.014 $ monthly. Lakshumi et al. (2006) presented the
results of study for the city of Chennai, India which has a population of 4.5
million. The aim was to determinate the optimal route for solid waste
collection and to compare the cost of new optimized and present routes. The
commercial software package ArcGIS was used with savings in length of
41.5% in day shift and 44% in night shift for one particular route.
One of the earliest applications of GIS for waste collection vehicle routing
was performed by Chang et al. (1997). They applied a revised multi-objective
programing model associated with GIS spatial analysis capabilities to analyze
and visualize optimal paths, and allocate vehicles and labor within a waste
collection network. They were able to analyze alternate solid waste collection
strategies under different planning scenarios to evaluate different planning
scenarios in the network to quickly gain a general understanding of the impact
of policy changes in the waste collection system. Among the authors
conclusions were that GIS will increasingly be relied on to support solid waste
management issues in the future.
Other studies have relied on other methodologies aside from GIS
functionality. Kim et al. (2006) and Sahoo et al. (2005) each report on the
development of a waste collection vehicle routing problem with time windows
(VRPTW) algorithm intended to reduce the number of vehicles and total
traveling time. The VRP is typically utilized in the waste collection industry to
reduce the number of vehicles and total traveling time. The authors also
considered route compactness since a solution with better route compactness
has fewer crossovers among routes. Their algorithm was successfully
implemented and deployed for real life commercial waste collection problems
at Waste Management (WM), Inc., the leading provider of comprehensive
