SIMWASTE
Integrated Household Solid Waste Management Simulator
Stephanie Sánchez Olaya
Sebastián Rojas Díaz
Department of Computer Science
Pontificia Universidad Javeriana
Bogotá, Colombia
[email protected]
Department of Computer Science
Pontificia Universidad Javeriana
Bogotá, Colombia
[email protected]
Abstract— Integrated solid waste management is an
important subject in terms of the challenging needs that urban
societies have not been able to supply, mainly due to the lack of
culture and conscience of people at this respect. SIM-WASTE is
an agent-based simulation model addressed to elementary schools
to use it as a didactic tool to teach children, between 2th and 5th
grade, how people behavior about solid waste management
drastically affects the environment due to the amount of
recyclable waste which ends up not being reused.
B. Specific objectives
 To make a characterization of different actors in the
IHSWM process.
 To develop an agent-based simulation model which
integrates all found variables in the characterization.
 To implement the model in the chosen agent-based
simulation platform NetLogo.
 To make a validation process of the model.
Keywords— Integrated solid waste management; agent-based
simulation; recycle; waste; human behaviour.
I.
INTRODUCTION
Solid waste management in big cities is an issue that
becomes more worrying every day, due to the contamination
attributed to the deficient system implemented for this matter.
This problem has been attacked in many ways, including
sophisticated mechanisms for the recollection and disposition
of waste. But it is clear that none of these formulas has the
expected environmental repercussion, since the problem
mainly lies in the human behavior at the generation of this
waste (Tchobanoglous, 1994).
In this manner, it is necessary to look for other kinds of
solutions that allow achieve a desirable and satisfactory state
for all the actors involved in this process, not sacrificing the
interests of them. From this need arises SIMWASTE as an
answer, attacking this problem from the educational
environment which may not show great short-term results, but
it is a contribution if it is implemented correctly in the basic
education system for big societies schools.
II.
OBJECTIVES
A. General objective
To develop a model that allows the agent-based simulation
and visualization of the Integrated Household Solid Waste
Management (IHSWM) in neighborhoods of 1st and 2nd
stratus in Bogotá, as a didactic tool. The case of study for the
implementation of the model is El Bosque neighborhood in the
locality of Usme, Bogotá.
III.
DEVELOPMENT PROCESS
A. Propoused methodology
Because this is a research project, it was necessary to propose
a methodology for the process based on the Scientific Method
with an engineering approach (González, 2012).
Question
formulation
Solution
creation
Test and
validation
Analysis and
synthesis
B. Proyect development
Initially a data recollection was made, through a poll applied
to a representative sample from the interest population, with
the purpose of getting information that would allow generating
more precision and exactitude in the results of the simulation
model. Simultaneously, there were a few meetings with
different actors involved in the whole process such as
representatives of ASOBEUM (Recyclers Association) and
representatives of UASEP (Public Utilities Special
Administrative Unity), where it was possible to get some
important information about the current waste recollection
system and some ideas to improve it. Later on, there was a
meeting with officials of the EAAP (Bogotá Water and
Sewerage Company) to get data about waste production and
management in the neighborhood case of study, and existing
district plans. From the data obtained, the construction of the
model was developed, the respective implementation and
validation with experts from all involved knowledge areas and
with final users.
C. Methodologic considerations
This project was made from the defined planning in the draft,
where it was established a set of activities and results that
would allow the right development. Nevertheless, during the
process it was necessary to make some adjustments to these
activities as for the time and date of assigned execution.
To better visualize the comparison between the estimations of
the draft and the real process, here it is presented a graphic
with each methodological phase of the project.
Post mortem Analysis
Estimated
Real
140
150
Figure 2: Introductory tool
120
80
80
50
60
30
B. Conceptual model
This model was designed taking advantage of the ODD
protocol which eases the transition from the conceptual
model to its implementation in NetLogo. Here it is
presented the order of the process to be performed in the
whole simulation (Volker Grimm, 2006).
Generatewaste
Setup
Bibliografic
compilation
Design
Construction
Validation
Figure 1: Post mortem analysis
IV.
Collectwhite-bags
Collectbalck-bags
Here are presented the entities, state variable and scales of the
model.
Name
Description
Person
Generates waste at home. This
-Beliefs
agent
Variables
-Intentions
executes
separation
and
dispossing processes.
Black bag
Agent
to
accumulate
ordinary
-Max. Capacity in Kg
Agent to accumulate recyclable
- Max. Capacity in Kg
waste.
White bag
A. Introductory tool
One of the most complicated decisions to be made during
this process was to decide the model granularity level,
namely, what oncoming level the waste management
process would present. Due to the spatial and dimensional
limitation because of the devices resolution characteristics
where the simulation is going to be executed, it was
necessary to separate the whole process and let the
separation process as a single model. An image of this
simulation is presented here.
Dispose
Figure 3: Processes execution
RESULTS
Results of this project are presented here where it is included
conceptual model and its validation with the implementation
of a functional prototype.
Separatewaste
waste.
Red bag
Agent to accumulate dangerous
- Max. Capacity in Kg
waste.
Colector truck
Agent to collect black bags.
-Collecting Schedule
-Collecting route
-Max weight capacity in kg
Recycler
Agent to collect white bags
-Collecting Schedule
-Collecting route
-Max weight capacity in kg
Animal
Wanders all around looking for
food and destroys black bags.
Property
Environment
where
waste
is
generated.
Neighborhood
Neighborhood of 1st and 2nd stratus
in Bogotá.
Temporal
One tick represents one second.
However, the speed of every tick
can be modified
V.
Figure 4: Agents, state variables and scales
Here are presented the processes executed in the simulation
and its executor.
Process
Executor
Description
Setup
Observer
Sets the initial configuration of the
Generate-waste
Person
Dispose
Person
Collect-back-bags
Collector truck
model.
Generates waste for each person in the
VALIDATION
Once the conceptual model was terminated and the prototype
validated most of it, validations with experts in agent-based
simulation, solid waste management and final users were
made. This was maybe the most important phase of the whole
process, due to the ratification of the successful development
of the model and the prototype. It was also possible to apply a
validation meeting with officials of UAESP, which gives so
much more reliability to the project.
neigborhood.
Each person dispose waste in the nearest
disposal point.
The truck chooses a route to collect the
black bags on its way.
Collect-white-bags
Recycler
Destroy-black-bags
Animal
The recycler chooses a route to collect
the white bags on his way.
Every animal in the simulation decides
to destroy or not the black bags on its
way.
Every person in the simulation has a utility objective which
pursues the satisfaction according to his or her beliefs and
desires. The utility formula is presented here.
𝑛
𝑈(𝑥) = ∑ 𝐵𝑏𝑖
VI.
CONCLUSIONS, RECOMMENDATIONS AND FUTURE WORK
A. Conclusions.
At the end of this project, there are several conclusions that
can help when developing an ABM.
Using Netlogo as a develop platform was very useful due to
the easy way of programming, interactivity, fast-learned, and
the complete documentation and support that exist.
Also, is very rewarding to learn an ABM oriented
programming language, which is very declarative and
intuitive. However, it can get difficult when trying to develop
complex algorithms.
Even when the simulation generated is close enough to the
real behavior of people in the area, would be necessary to keep
in mind other environmental variables in order to get more
accurate results if use for support decision making purposes.
𝑖=0
•
𝑈(𝑥) : Value to be maximized
•
𝐵𝑏 : White bags generated
•
𝑛 : Number of people
C. Functional prototype
The implementation of the model was made in NetLogo
(Railsback & Grimm, 2012), where it was easy to
visualize the behavior of each agent and to validate the
built conceptual model. Here is presented an image of the
final developed prototype.
B. Recommendation
The ABM can be very complex and powerful, for that reason
in order to obtain better result, would be necessary to make a
more rigorous and formal calibration of the model, with data
of the environment much more accurate.
Even when Netlogo is a powerful tool, it has some graphics
limitations that do not allow importing images to create
different kinds of agents nor personalize user messages.
Netlogo has several extensions to simplify the work. One of
them is called GraphStream which is very useful when
working with graphs. This extension allow to create a graph of
agents in Netlogo and send it to Eclipse Java where you are
able to apply some algorithms to process graphs, and at the
end, send it back to Netlogo.
C. Future work
Include a bad management of their waste, which would
simulate people putting waste on the wrong bag, and showing
the impact that this has in the system
Include algorithms that allow optimizing the path the truck
take to collect the waste.
Show the behavior of a person who does not separate his
waste when is located right next to one who does.
Figure 5: Functional prototype
ACKNOWLEDGMENT
We want to thank in the first place, to our parents who have
supported us along our studies in order to accomplish our
goals.
We also want to thank to our director, Ing. Oscar Xavier
Chavarro Garcia, who trusted us and advised us while working
on this project.
We want to thank all the amazing people involved in this
project who gave us their support and knowledge. Ing. Sandra
Mendez specialist in solid waste management. Ing. Rafael
Gonzalez specialist in ABM models. Ing. Alex Linares who
helped in the fieldwork with PROSOFI (Javeriana, 2013), and
professor Monica Brijaldo specialist in education.
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