For our MSCI 332 presentation/final project we decided to tackle minimizing elderly care wait list time using mixed integer programming. Fun project!
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Msci 332 presentation - Minimizing Elderly Care Wait list Time
1. Using optimization to minimize
NURSING CARE
w a i t l i s t t i m e
By Nor Hameed, Merisa Lee, Masa Shaban & Yahya Wahbeh
2. PROBLEM
Between 2005 and 2012, the median wait
time for people trying to get into an
Ontario nursing home almost tripled
from 36 to 98 days.
15% of people on nursing home wait lists
die before they can be placed.
3. Projected number of Canadians over 65 in percentage
Life expectancy is steadily increasing due to improved health
services and the retirement of baby boomers.
8. Elmira
(3)
Cambridge
(8)
Waterloo
(3)
Kitchener
(8)
Split into 4 different clusters based on location
9. Basic Deluxe Private
Cluster
Total #
available
beds
# waiting
Average
waiting
time
# waiting
Average
waiting
time
# waiting
Average
waiting
time
Cambridge 336 486 917 29 190 180 591
Kitchener 468 1178 917 85 331 912 679
Waterloo 108 268 677 2 168 311 1305
Elmira 60 36 357 12 127 12 171
10. Objective function:
Minimize waiting time
subject to:
0<xT<0.4*total capacity
xB*cB + xD*cD + xP*cP <xT
cB + cD + cP = 1
2
=0
=0
訣
11. XT
1 AB0
M1 M2
W0
DW0
D0 0
AB1
W1
DW1
D1
M0
ABi = average of available beds at year i
Wi = average number of waiting days at year i
DWi = average days waiting per patient at year i
Di = demand at year i
Mi = mortality at year i
2
12. What percentage for new capacity added
should we allocate each bed type?
? ? ?
Demand Capacity
xB
xD xP
xB
xD
xP