Topic 2 Demand Forecasting Models I(1)
-
Upload
chaitanyakumar -
Category
Documents
-
view
234 -
download
0
Transcript of Topic 2 Demand Forecasting Models I(1)
-
8/11/2019 Topic 2 Demand Forecasting Models I(1)
1/26
Time Period Demand
1 84
2 81
3 89
4 90
5 996 106
7 127
8 117
9 127
10 103
11 96
12 96
13 86
14 101
15 10916
1 2 3 4 5 6
60
70
80
90
100
110
120
130
140
Dema
Ti
Demand
-
8/11/2019 Topic 2 Demand Forecasting Models I(1)
2/26
-
8/11/2019 Topic 2 Demand Forecasting Models I(1)
3/26
Time Period Demand Last Period Forecast
1 84
2 81 84
3 89 81
4 90 89
5 99 90
6 106 99
7 127 106
8 117 127
9 127 117
10 103 127
11 96 103
12 96 96
13 86 96
14 101 86
15 109 101
16 109
Comment:This method is the navie method of forecast with maximum errors
its a short term forecast(not feasable)
0
20
40
60
80
100
120
140
Quantity
-
8/11/2019 Topic 2 Demand Forecasting Models I(1)
4/26
Last Period Forecast
Demand
Last Period Forecast
Time Period
-
8/11/2019 Topic 2 Demand Forecasting Models I(1)
5/26
-
8/11/2019 Topic 2 Demand Forecasting Models I(1)
6/26
Make Col D +ve Column F /Column B
3 3.70# 3.70#
8 8.99# 6.35#
1 1.11# 4.60#
9 9.09# 5.72#
7 6.60# 5.90#
21 16.54# 7.67#
10 8.55# 7.80#10 7.87# 7.81#
24 23.30# 9.53#
7 7.29# 9.30#
0 0.00# 8.46#
10 11.63# 8.72#
15 14.85# 9.19#
8 7.34# 9.06#
MD MPE
9.5 9.06#
st error can be 0 ,it doesnt mean yor forecast is corr
Column ! running
average
"soluteForecast Error
"solute PercentError
Mean "solutePercent Error
(MPE)
-
8/11/2019 Topic 2 Demand Forecasting Models I(1)
7/26
Col D running total Col F running total Col # / Col $
MD
-3 3 3.0 -1.00
5 11 5.5 0.91
6 12 4.0 1.50
15 21 5.3 2.86
22 28 5.6 3.93
43 49 8.2 5.27
33 59 8.4 3.9243 69 8.6 4.99
19 93 10.3 1.84
12 100 10.0 1.20
12 100 9.1 1.32
2 110 9.2 0.22
17 125 9.6 1.77
25 133 9.5 2.63
ect, ha!ent met the demand acta""y
Col F runningaverage
CumulativeForecast Error
Cumulative"solute
Forecast ErrorTracking%ignal
-
8/11/2019 Topic 2 Demand Forecasting Models I(1)
8/26
Time Period Demand
1 84
2 813 89 82.5
4 90 85.0 8.!
5 99 8".5 8#.!
6 106 ".5 "2.!
7 127 $02.5 "8.%
8 117 $$#.5 $$0.!
9 127 $22.0 $$#.!
10 103 $22.0 $2%.!
11 96 $$5.0 $$5.!
12 96 "".5 $08.!13 86 "#.0 "8.%
14 101 "$.0 "2.!
15 109 "%.5 ".%
16 $05.0 "8.!
&E'!E 100.7 101.0 101.7
M##MM 81.0 82.5 84.7
M*#MM 127.0 122.0 123.7
Two PeriodMoving Average
Forecast
Three PeriodMoving Average
Forecast
Fore
cast
1 2 3 4 5 6 7 8 9 10 11
0
20
40
60
80
100
120
140
Moving Av
Time Period
Quantity(units)
-
8/11/2019 Topic 2 Demand Forecasting Models I(1)
9/26
$ 2 % 5 # ! 8 " $0 $$ $20.0
20.0
0.0
#0.0
80.0
$00.0$20.0
$0.0
Moving Ave
Time Period
Demand/
-
8/11/2019 Topic 2 Demand Forecasting Models I(1)
10/26
8#.0
8".8
"#.0
$05.5
$$2.%
$$".%
$$8.5
$$0.8$05.5
"5.%
".8
"8.0
102.6
86.0
119.3
Four PeriodMoving Average
Forecast
12 13 14 15 16
rage Forecasts
Demand
Moving average
(Demand)
Moving average
(Demand)
-
8/11/2019 Topic 2 Demand Forecasting Models I(1)
11/26
$% $ $5 $#
rage
&emand
Two 'eriod (ovin) *vera)e+orecast
Three 'eriod (ovin) *vera)e+orecast
+our 'eriod (ovin) *vera)e+orecast
-
8/11/2019 Topic 2 Demand Forecasting Models I(1)
12/26
Time Period Demand
1 84 eig,ts
2 81 t-. is 01
3 89 t-1 is 0.
4 90 85.# t-2 is 035 99 8!."
6 106 ".%
7 127 $00.!
8 117 $$5.$
9 127 $$!.8
10 103 $2
11 96 $$%
12 96 $0.%
13 86 "!.
14 101 "$15 109 "5.5
16 $02
T,ree-4eriod 5eig,ted
moving average 6orecast
1 2 3 4 5 6 7 8 9 10 11 12 13
0
20
40
60
80
100
120
140
3-Period Weighted A
Periods
Demand/Forecast
-
8/11/2019 Topic 2 Demand Forecasting Models I(1)
13/26
14 15 16
erage
Demand
!ree"#eriod $eig!ted moving
average %orecast
-
8/11/2019 Topic 2 Demand Forecasting Models I(1)
14/26
Time Period Demand
1 24
2 26
3 22 25.0 25.04 25 2. 22.#
5 19 2.5 2.5
6 31 2%. 20.$
7 26 2." 28.8
8 18 25.$ 2#.#
9 29 2%.! $".!
10 24 2.8 2!.$
11 30 2.# 2.#
12 23 25.! 28."
13 25.2 2.2
Exponential SmoothingForecast with alpha = 0!
Exponential SmoothingForecast with alpha = 0"
1 2 3 4 5 6 7 8 9 10 11 12
0&0
5&0
10&0
15&0
20&0
25&0
30&0
35&0
!"onentia# $moothing
Time Period
Demand/Forecast
-
8/11/2019 Topic 2 Demand Forecasting Models I(1)
15/26
,-* ,-*
2 2 +or ex/onential smoothin(-*) o to data analsis and select ex/onential smo
2. 2. 1elect the demand coloumn
2%."2 2%."2 the value of alfa is iven in dam/in factor
2.$%# 2.$%# if alfa is .2 then dam/in factor is 0.8
2%.$088 2%.$088 out /ut rane is the couloun where ou want forecast
2.#8!0 2.#8!0
2.""#% 2.""#%
2%.55"!$ 2%.55"!$
2.#!!# 2.#!!#
2.5$82$ 2.5$82$
25.#$5! 25.#$5!
13
Demand
'#onentia *moot!ing Forecast $it!
a#!a + 0&2
'#onentia *moot!ing Forecast $it!
a#!a + 0&8
-
8/11/2019 Topic 2 Demand Forecasting Models I(1)
16/26
othin
-
8/11/2019 Topic 2 Demand Forecasting Models I(1)
17/26
l4,a 01
Period Demand
1 102 11 $0.00
3 9 $0.204 11 "."#
5 10 $0.$!
6 8 $0.$%
7 12 ".!$
8 9 $0.$!9 10 "."%
10 11 "."5
11 20 $0.$#12 11 $2.$%
13 9 $$."0
14 11 $$.%2
15 10 $$.2#16 9 $$.0$
17 11 $0.#018 4 $0.#8
19 10 ".%520 11 ".8
l4,a 07
Period Demand
1 10
2 11 $0.0
3 9 $0.84 11 ".
5 10 $0.!
6 8 $0.$
7 12 8.
8 9 $$.%9 10 ".5
10 11 "."11 20 $0.8
12 11 $8.213 9 $2.
E84onential
%moot,ing
Forecast
E84onential
%moot,ing
Forecast
1 2 3 4 5 6
0
5
10
15
20
25
!
)a#ue
10
15
20
25
!"on
-
8/11/2019 Topic 2 Demand Forecasting Models I(1)
18/26
14 11 ".!
15 10 $0.!16 9 $0.$
17 11 ".218 4 $0.#
19 10 5.%20 11 ".$
1 2 3 4 5 6 7 8 9
0
5
-
8/11/2019 Topic 2 Demand Forecasting Models I(1)
19/26
7 8 9 10 11 12 13 14 15 16 17 18 19 20
onentia# $moothing (A#"ha % &')
,ct-a Forecast
Data Point
s/ie in demand
di/ in demand
ntia# $moothing (A#"ha % &'*)
Demand
'#onentia *moot!ing Forecast
-
8/11/2019 Topic 2 Demand Forecasting Models I(1)
20/26
10 11 12 13 14 15 16 17 18 19 20
-
8/11/2019 Topic 2 Demand Forecasting Models I(1)
21/26
$"%ha 01
Period Demand
1 10 ,-*2 11 $0
3 9 $0.24 11 "."#
5 10 $0.$#8
6 8 $0.$%
7 12 ".!0!52
8 9 $0.$##0$#9 10 "."%28$28
10 11 "."#2502
11 20 $0.$5!000$"212 21 $2.$25#00$5%#
13 19 $%."0080$22"
14 22 $."20%80"8%
15 18 $#.%%#%0!2!8#16 20 $#.##"05822"
17 21 $!.%%52%##58%18 19 $8.0#8$8"%2#!
19 20 $8.2555$#$%20 21 $8.#0%#$$#"$
E84onential
%moot,ing
Forecast
1 2 3 4 5 6 7 8
0
5
10
15
20
25
!"on
D
)a#ue
-
8/11/2019 Topic 2 Demand Forecasting Models I(1)
22/26
9 10 11 12 13 14 15 16 17 18 19 20
ntia# $moothing (A#"ha % &')
,ct-a Forecast
ta Point
sustained increase in demand
low al/ha means slow reaction time
-
8/11/2019 Topic 2 Demand Forecasting Models I(1)
23/26
$"%ha 07
Period Demand
1 10 ,-*2 11 $0.00
3 9 $0.804 11 ".%#
5 10 $0.#!
6 8 $0.$%
7 12 8.%
8 9 $$.2"9 10 ".#
10 11 ".8"
11 20 $0.!812 21 $8.$#
13 19 20.%
14 22 $".2"
15 18 2$.#16 20 $8.#"
17 21 $".!18 19 20.!5
19 20 $".%520 21 $".8!
E84onential
%moot,ing
Forecast
1 2 3 4 5 6 7
0
5
10
15
20
25
!"on
P
)a#ue
-
8/11/2019 Topic 2 Demand Forecasting Models I(1)
24/26
9 10 11 12 13 14 15 16 17 18 19 20
ntia# $moothing (A#"ha % &'*)
,ct-a Forecast
riod
same trend as /revious sheet
hiher al/ha sees faster reaction to increase in trend
-
8/11/2019 Topic 2 Demand Forecasting Models I(1)
25/26
Month Actual Demand
$ $2
2 $!
% 20
$"
5 2
# 2$
! %$8 28
" %#
$0
1 2 3 4 5 6 7 8 9 100
5
10
15
20
25
30
35
40
%() + 2&55 . 10&3611111111
,ct-a Deman
Linear (,ct-a
Demand)
Month
A
ctua#Demand
-
8/11/2019 Topic 2 Demand Forecasting Models I(1)
26/26
d