Visiting PhD student, Morgane Dumont presented on how to improve the order of evolutionary models in agent-based simulations for population dynamics as part of the SMART Seminar Series on 15 December 2017. More information: http://www.uoweis.co/event/how-to-improve-the-order-of-evolutionary-models-in-agent-based-simulations-for-population-dynamics/ Keep updated with future events: http://www.uoweis.co/tag/smart-infrastructure/

1. Preliminary step
Calendar-based approach
Results
Conclusion
Future Work
How to improve the order of evolutionary models in
agent-based simulations for population dynamics
M. Dumont 1 J. Barthélemy 2 N. Huynh 2 T. Carletti 1
1naXys - University of Namur, Belgium
2SMART - University of Wollongong, Australia
SMART, December 2017
Namur Institute for Complex
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2. Preliminary step
Calendar-based approach
Results
Conclusion
Future Work
Context
My main research topic : Virtual Belgium In Health (VBIH)
Create a tool forecasting the Belgian population until 2030 and the health
needs of elderlies in this population.
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3. Preliminary step
Calendar-based approach
Results
Conclusion
Future Work
Summary
1 Preliminary step
2 Calendar-based approach
3 Results
4 Conclusion
5 Future Work
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4. Preliminary step
Calendar-based approach
Results
Conclusion
Future Work
Conference paper for the preliminary step
Reference paper
M. Dumont, J. Barthélemy, T. Carletti and N. Huynh (2017), Importance
of the order of the modules in TransMob [Huynh et al., 2015].
In Syme, G., Hatton MacDonald, D., Fulton, B. and Piantadosi, J. (eds)
MODSIM2017, 22nd International Congress on Modelling and Simulation.
Modelling and Simulation Society of Australia and New Zealand,
December 2017, pp. 811-817. ISBN: 978-0-9872143-7-9
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5. Preliminary step
Calendar-based approach
Results
Conclusion
Future Work
TransMob
Reference paper
N. Huynh, P. Perez, M. Berryman and J. Barthélemy (2015), Simulating
Transport and Land Use Interdependencies for Strategic Urban Planning -
An Agent Based Modelling Approach, Systems
3 Local government areas of New South Wales
28 suburbs +/- 180,000 inhabitants in 2011
68 Km2
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6. Preliminary step
Calendar-based approach
Results
Conclusion
Future Work
Figure : Flowchart from the paper
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7. Preliminary step
Calendar-based approach
Results
Conclusion
Future Work
Figure : Flowchart from the paper
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8. Preliminary step
Calendar-based approach
Results
Conclusion
Future Work
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9. Preliminary step
Calendar-based approach
Results
Conclusion
Future Work
Number of possible combinations
All possible permutations of the 5 processes:
Ageing
Death
Divorce
Birth
Marriage
Only orders with birth after ageing
Simulation
60 orders and 20 seeds for the random number generator
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10. Preliminary step
Calendar-based approach
Results
Conclusion
Future Work
Stability for 20 seeds and the 60 admissible orders
Figure : Average and range of the simulated population
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11. Preliminary step
Calendar-based approach
Results
Conclusion
Future Work
ANOVA (confidence = 95%)
The order of the dynamical processes does influence the average final
simulated population.
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12. Preliminary step
Calendar-based approach
Results
Conclusion
Future Work
ANOVA (confidence = 95%)
The order of the dynamical processes does influence the average final
simulated population.
Principal component Analysis
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13. Preliminary step
Calendar-based approach
Results
Conclusion
Future Work
ANOVA (confidence = 95%)
The order of the dynamical processes does influence the average final
simulated population.
Principal component Analysis
Classification
Class 1: Ageing before death
Class 2: Death before ageing
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14. Preliminary step
Calendar-based approach
Results
Conclusion
Future Work
Classification results
Legend
Class 1:
Ageing before death
Class 2:
Death before ageing
0 2 4 6 8 10
37383940
Year after 2011
Averageage
Class 1
Class 2
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15. Preliminary step
Calendar-based approach
Results
Conclusion
Future Work
Classification results
Legend
Class 1: Ageing before death Class 2: Death before ageing
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16. Preliminary step
Calendar-based approach
Results
Conclusion
Future Work
Summary of the preliminary analysis
The order significantly influences the results
Ageing before death ⇒ smaller and younger population
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17. Preliminary step
Calendar-based approach
Results
Conclusion
Future Work
Proposition to reduce the variability caused by the order
Intuition
Relative position of death and ageing influences the results
⇒ We fix these processes using birthday and date of death
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18. Preliminary step
Calendar-based approach
Results
Conclusion
Future Work
Proposition to reduce the variability caused by the order
Intuition
Relative position of death and ageing influences the results
⇒ We fix these processes using birthday and date of death
Birthday: split the year in before and after birth day
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19. Preliminary step
Calendar-based approach
Results
Conclusion
Future Work
Proposition to reduce the variability caused by the order
Intuition
Relative position of death and ageing influences the results
⇒ We fix these processes using birthday and date of death
Birthday: split the year in before and after birth day
Death date: determine the date of death for people dying this year
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20. Preliminary step
Calendar-based approach
Results
Conclusion
Future Work
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21. Preliminary step
Calendar-based approach
Results
Conclusion
Future Work
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22. Preliminary step
Calendar-based approach
Results
Conclusion
Future Work
Need of probabilities of events before and after birthday
Probability of event E during the year:
P(E) = P(E before BD or E after BD)
= P(E before BD ) + P(E after BD)
With BD = the number of days from 1st of January to the birthday.
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23. Preliminary step
Calendar-based approach
Results
Conclusion
Future Work
If the distribution of the event occuring each day of the year is known,
P(E before BD =
BD
i=1
P(E on day i)
and
P(E after BD ) =
365
i=BD+1
P(E on day i).
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24. Preliminary step
Calendar-based approach
Results
Conclusion
Future Work
Assuming that E follows a uniform distribution :
P(E on day i) =
P(E|A)
365
with P(E|A) the probability of the event for an individual during the
whole year while he is of age A.
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25. Preliminary step
Calendar-based approach
Results
Conclusion
Future Work
Assuming that E follows a uniform distribution :
P(E on day i) =
P(E|A)
365
with P(E|A) the probability of the event for an individual during the
whole year while he is of age A.
And:
P(E) = P(E|A) ∗
BD
365
+ P(E|A + 1) ∗
365 − BD
365
.
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26. Preliminary step
Calendar-based approach
Results
Conclusion
Future Work
Numerical experiments - simulations
We consider all possible permutations of the 3 processes:
Divorce
Birth
Marriage
Simulation
6 orders and 20 seeds for the random number generator
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27. Preliminary step
Calendar-based approach
Results
Conclusion
Future Work
Comparison
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28. Preliminary step
Calendar-based approach
Results
Conclusion
Future Work
Comparison with the classes of standard approach
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29. Preliminary step
Calendar-based approach
Results
Conclusion
Future Work
Comparison with the classes of standard approach
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30. Preliminary step
Calendar-based approach
Results
Conclusion
Future Work
Does the order in the proposed approach have an impact?
We define variables for the order:
Posdivorce = position of divorce in the process
Posmarriage = position of marriage in the process
Posbirth = position of birth in the process
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31. Preliminary step
Calendar-based approach
Results
Conclusion
Future Work
Variables for the population after 10 simulated years
Gender:
Number of women after 10 years;
Number of men after 10 years;
Age:
Number of less than 30 years old after 10 years;
Number of 31-60 years old after 10 years;
Number of more than 61 years old after 10 years.
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32. Preliminary step
Calendar-based approach
Results
Conclusion
Future Work
Importance of the order
Step 1 : Classification of the variables concerning the final population.
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33. Preliminary step
Calendar-based approach
Results
Conclusion
Future Work
Importance of the order
Step 1 : Classification of the variables concerning the final population.
K-means
Minimises the variance intra-classes
and maximises the variance
between classes. (here : 2 classes)
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34. Preliminary step
Calendar-based approach
Results
Conclusion
Future Work
Importance of the order
Step 1 : Classification of the variables concerning the final population.
K-means
Minimises the variance intra-classes
and maximises the variance
between classes. (here : 2 classes)
Principal Component Analysis
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35. Preliminary step
Calendar-based approach
Results
Conclusion
Future Work
Comparison of the classifications
Standard approach
Calendar-based approach
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36. Preliminary step
Calendar-based approach
Results
Conclusion
Future Work
Importance of the order
Step 2 : Try to identify patterns in the orders for the simulations in the
same class.
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37. Preliminary step
Calendar-based approach
Results
Conclusion
Future Work
Importance of the order
Step 2 : Try to identify patterns in the orders for the simulations in the
same class.
Decision tree ⇒ relative order of marriage and birth
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38. Preliminary step
Calendar-based approach
Results
Conclusion
Future Work
Importance of the order
Step 2 : Try to identify patterns in the orders for the simulations in the
same class.
Decision tree ⇒ relative order of marriage and birth
First Model Second Model Third Model Class 1 Class 2
Marriage Divorce Birth 16 4
Marriage Birth Divorce 20 0
Divorce Marriage Birth 19 1
Divorce Birth Marriage 0 20
Birth Divorce Marriage 1 19
Birth Marriage Divorce 2 18
Table : Classification of orders with the addition of dates
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39. Preliminary step
Calendar-based approach
Results
Conclusion
Future Work
Importance of the order
Step 2 : Try to identify patterns in the orders for the simulations in the
same class.
Decision tree ⇒ relative order of marriage and birth
First Model Second Model Third Model Class 1 Class 2
Marriage Divorce Birth 16 4
Marriage Birth Divorce 20 0
Divorce Marriage Birth 19 1
Divorce Birth Marriage 0 20
Birth Divorce Marriage 1 19
Birth Marriage Divorce 2 18
Table : Classification of orders with the addition of dates
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40. Preliminary step
Calendar-based approach
Results
Conclusion
Future Work
Conclusion
1 The order of the models influences the results
2 Relative position of ageing and death
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41. Preliminary step
Calendar-based approach
Results
Conclusion
Future Work
Conclusion
1 The order of the models influences the results
2 Relative position of ageing and death
⇒ Calendar-based approach to fix these two events:
1 Decrease of the variability of the simulation
2 Follow the larger classes of standard approach but equilibrated for
elderlies
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42. Preliminary step
Calendar-based approach
Results
Conclusion
Future Work
Conclusion
1 The order of the models influences the results
2 Relative position of ageing and death
⇒ Calendar-based approach to fix these two events:
1 Decrease of the variability of the simulation
2 Follow the larger classes of standard approach but equilibrated for
elderlies
JASS submitted paper
Towards the Right Ordering of the Sequence of Models for the Evolution
of a Population Using Agent-Based Simulation, Morgane Dumont, Johan
Barthelemy, Nam Huynh and Timoteo Carletti
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43. Preliminary step
Calendar-based approach
Results
Conclusion
Future Work
Future Work
Suggestion from Arnaud Banos:
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44. Preliminary step
Calendar-based approach
Results
Conclusion
Future Work
Acknowledgement
SMART (Pascal, Tania and the whole staff).
This research used resources of the "Plateforme Technologique de
Calcul Intensif(PTCI)" (http://www.ptci.unamur.be) located at the
University of Namur, Belgium, which is supported by the
F.R.S.-FNRS under the convention No. 2.5020.11.
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45. Preliminary step
Calendar-based approach
Results
Conclusion
Future Work
Thanks for your attention !
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