2.  Introduction
 Aims & Objectives
 Data Acquisition & Creation of Network
Dataset
 Finding the best route using a Network
Dataset
 Results
 Summary/Conclusion
 Next steps

3.  Waste Collection contibutes a vast majority of
total municipal solid waste (MSW)
management cost worldwide.
 The evoluton of GIS as an intelligent spatial
tool makes it imperative to develop a model
to assist decision makers analyse and
optimise collection routes time saving MSW
costs on salaries and fuel.

4.  Exploring the possibilities of ArcGIS 10.1
for optimizing council’s solid waste
collection system
 Using Network Analyst Extension to execute
the optimization of collection routes

5.  Sources of Data (North Ayshire Local Council,
Ordinance Survey, UK Borders Digimap)
 Customers’ locations
 Transportation Geodatabase
 Landfill sites (Residual Waste, Recycled Waste & and Food
Waste/Garden Waste
Restrictions to the dataset needed however made this presentation
centric on San Francisco geodatabase which holds transportation feature
dataset needed for this analysis.

7. o ArcCatalog is used here to
prepare the Network Dataset
o The street layer has some
elevation fields which can be
considered i.e. historical traffic
data, road types, average speed on
certain roads and restriction
attributes; One-way roads, dual
carriage ways, U-turns allowed etc
o Evaluators can be created
from the attributes of the dataset
specifying restrictions that should be
permitted
o Blue Cirlces shows which attribute
will be considered when process is run

12.  This presentation showed how to incorporate a
GIS model to for the optimization of MSW.
The model used transportation geodatabase
dataset (historical traffic data, road types, speed
limits and road restriction attributes)
 The result is cost effective to the council in
terms of annual savings made due to shorter
distances travelled from customer’s addresses to
landfill sites and also collection time of refuse
taking live traffic data into consideration.