SlideShare a Scribd company logo
Operations Research
Chapter : Transportation
Find Initial Basic Feasible Solution-IBFS Using
North West Corner Method-- NWCM ,
Least Cost Method-- LCM and
Vogel’s Approximation Method-- VAM
Optimality Test using Modified Distribution Method-
MODI method.
Variation in transportation
Unbalance Supply and Demand
Degeneracy and its resolution
Maximization Problem
Introduction
• Transportation Models are used to find out optimum cost of
transportation of goods.
• Company ABC has three plants at Ahmedabad, Surat and Rajkot and
four demand stations at Visnagar, Baroda and Vapi and Bhuj. We
can formulate transportation matrix as below
Visnagar Baroda Vapi Bhuj Capacity
Ahmedabad 10 20 30 40 7
Surat 20 30 10 60 8
Rajkot 20 15 40 20 5
Demand 2 7 6 5 20
Here,
In table cell value 10,20,30,40 Rs. shows cost of transportation.
Last column value shows daily maximum supply.
Last row value shows daily maximum demand of each city.
Terms:
1) Balanced Model
If, Total Supply=Total Demand
2) Non Degenerate Solution
If, m+n-1=number of allocated cell
Where,
m=total number of rows
n=total number of columns
3) Feasible solution
All supply and demand constraints are satisfied.
Methods to find out Initial Basic Feasible Solution (IBFS):
1. NWCM-- North West Corner Method
2. LCM-- Least Cost Method
3. VAM-- Vogel’s Approximation Method
Example 1 : (Problem Type: Balanced Problem)
A Company has 3 production facilities S1, S2 and S3 with
production capacity of 7, 9 and 18 units per week of a product,
respectively.
These units are to be shipped to 4 warehouses D1, D2, D3 and
D4 with requirement of 5,6,7 and 14 units per week,
respectively.
The transportation costs (in rupees) per unit between factories
to warehouses are given in the table below.
D1 D2 D3 D4 Capacity
S1 19 30 50 10 7
S2 70 30 40 60 9
S3 40 8 70 20 18
Demand 5 8 7 14 34
Find initial basic feasible solution for given problem by using
North-West corner method
if the object is to minimize the total transportation cost.
Demand Destination
D1 D2 D3 D4 Supply
Supply
Station
S1 19 (5) 30 50 10 7
S2 70 30 40 60 9
S3 40 8 70 20 18
Demand 5 8 7 14 34/34
Solution:
North-West corner method---NWCM
Step 1 : Identify North west corner from all cost cell.
Here S1D1 is North west corner.
Do allocation in this cell.
Demand of D1 = 5 which is less than possible supply from S1= 7. Here
5<7...So allocate (5) in S1D1 Cell.
Demand Destination
D1 D2 D3 D4 Supply
Supply
Station
S1 19 (5) 30 (2) 50 10 7
S2 70 30 40 60 9
S3 40 8 70 20 18
Demand 5 8 7 14 34/34
•Step 2 : Now no need to consider D1 column as its demand 5 is
completed.
• Identify North west corner from all remaining cost cell.
•Here S1D2 is North west corner.
• Do allocation in this cell.
•Demand of D1 = 8. Available supply from S1=7-5=2 Here, 2<8...So
allocate (2) in S1D2 Cell.
Demand Destination
D1 D2 D3 D4 Supply
Supply
Station
S1 19 (5) 30 (2) 50 10 7
S2 70 30 (6) 40 60 9
S3 40 8 70 20 18
Demand 5 8 7 14 34/34
•Step 3 : Now no need to consider D1 column and S1 row.As its
constraints 5 and 7 are satisfied.
• Identify North west corner from all remaining cost cell...Here S2D2 is
North west corner.
• Do allocation in this cell.
•Remaining Demand of D2 = 8-2 =6. Possible supply from S2=9. Here,
6<9..So allocate (6) in S2D2 Cell.
Demand Destination
D1 D2 D3 D4 Supply
Supply
Station
S1 19 (5) 30 (2) 50 10 7
S2 70 30 (6) 40 (3) 60 9
S3 40 8 70 20 18
Demand 5 8 7 14 34/34
•Step 4 : Now no need to consider D1-D2 column and S1 row.
• Identify North west corner from all remaining cost cell.
•Here S2D3 is North west corner.
• Do allocation in this cell.
•Demand of D3 = 7. Available supply from S2=9-6=3. Here, 3<7..So
allocate (3) in S2D3 Cell.
Demand Destination
D1 D2 D3 D4 Supply
Supply
Station
S1 19 (5) 30 (2) 50 10 7
S2 70 30 (6) 40 (3) 60 9
S3 40 8 70 (4) 20 18
Demand 5 8 7 14 34/34
•Step 5 : Now no need to consider D1-D2 column and S1-S2 row.
• Identify North west corner from all remaining cost cell.
•Here S3D3 is North west corner.
• Do allocation in this cell.
•Remaining Demand of D3 = 7-3=4 . Possible supply from S2=18. So
allocate (4) in S3D3 Cell.
Demand Destination
D1 D2 D3 D4 Supply
Supply
Station
S1 19 (5) 30 (2) 50 10 7
S2 70 30 (6) 40 (3) 60 9
S3 40 8 70 (4) 20 (14) 18
Demand 5 8 7 14 34/34
•Step 6 : Here remaining cell is S3D4.
• Do allocation in this cell.
•Demand of D3 = 14 .
• Possible supply from S3=18-4=14.
•So allocate (14) in S3D4 Cell.
From previous table,
The minimum total transportation cost =
(19×5)+(30×2)+(30×6)+(40×3)+(70×4)+(20×14)
=1015 Rs.--------Answer.
Here,
the number of allocated cells = 6
is equal to
m + n - 1 = 3 + 4 - 1 = 6
So,
∴ This solution is non-degenerate----Answer.
Where, m= total rows = 3.
n= total columns = 4.
Example 2:
(Similar as example 1 NWCM METHOD)
Find Solution using North-West Corner method
D1 D2 D3 D4 Supply
S1 11 13 17 14 250
S2 16 18 14 10 300
S3 21 24 13 10 400
Demand 200 225 275 250 950/950
Type-Balanced supply and demand
D1 D2 D3 D4 Supply
S1 11 (200) 13 17 14 250
S2 16 18 14 10 300
S3 21 24 13 10 400
Demand 200 225 275 250
D1 D2 D3 D4 Supply
S1 11 (200) 13 (50) 17 14 250
S2 16 18 14 10 300
S3 21 24 13 10 400
Demand 200 225 275 250
D1 D2 D3 D4 Supply
S1 11 (200) 13 (50) 17 14 250
S2 16 18 (175) 14 10 300
S3 21 24 13 10 400
Demand 200 225 275 250
D1 D2 D3 D4 Supply
S1 11 (200) 13 (50) 17 14 250
S2 16 18 (175) 14 (125) 10 300
S3 21 24 13 10 400
Demand 200 225 275 250
D1 D2 D3 D4 Supply
S1 11 (200) 13 (50) 17 14 250
S2 16 18 (175) 14 (125) 10 300
S3 21 24 13 (150) 10 400
Demand 200 225 275 250
D1 D2 D3 D4 Supply
S1 11 (200) 13 (50) 17 14 250
S2 16 18 (175) 14 (125) 10 300
S3 21 24 13 (150) 10 (250) 400
Demand 200 225 275 250
The minimum total transportation cost =
(11×200) +(13×50)+(18×175)+(14×125)+(13×150)+(10×250)
=12200
Here,
the number of allocated cells = 6
is equal to
m + n - 1 = 3 + 4 - 1 = 6
∴ This solution is non-degenerate
Example 3 (Problem Type-Unbalanced supply and demand
example)
Find Solution using North-West Corner method
D1 D2 D3 Supply
S1 4 8 8 76
S2 16 24 16 82
S3 8 16 24 77
Demand 72 102 41
Here Total Demand = 215 is less than Total Supply = 235
D1 D2 D3 Ddummy Supply
S1 4 8 8 0 76
S2 16 24 16 0 82
S3 8 16 24 0 77
Demand 72 102 41 20
So
add a dummy demand column
with 0 unit cost with allocation 20.
Now, the modified table is
D1 D2 D3 Ddummy Supply
S1 4 (72) 8 8 0 76
S2 16 24 16 0 82
S3 8 16 24 0 77
Demand 72 102 41 20
D1 D2 D3 Ddummy Supply
S1 4 (72) 8 (4) 8 0 76
S2 16 24 16 0 82
S3 8 16 24 0 77
Demand 72 102 41 20
D1 D2 D3 Ddummy Supply
S1 4 (72) 8 (4) 8 0 76
S2 16 24 (82) 16 0 82
S3 8 16 24 0 77
Demand 72 102 41 20
D1 D2 D3 Ddummy Supply
S1 4 (72) 8 (4) 8 0 76
S2 16 24 (82) 16 0 82
S3 8 16 (16) 24 0 77
Demand 72 102 41 20
D1 D2 D3 Ddummy Supply
S1 4 (72) 8 (4) 8 0 76
S2 16 24 (82) 16 0 82
S3 8 16 (16) 24 (41) 0 77
Demand 72 102 41 20
D1 D2 D3 Ddummy Supply
S1 4 (72) 8 (4) 8 0 76
S2 16 24 (82) 16 0 82
S3 8 16 (16) 24 (41) 0 (20) 77
Demand 72 102 41 20
Initial feasible solution ----IBFS is
The minimum total transportation cost
=(4×72)+(8×4)+(24×82)+(16×16)+(24×41)+(0×20)=3528
Here, the number of allocated cells = 6
is equal to
m + n - 1 = 3 + 4 - 1 = 6
∴ This solution is non-degenerate
Example 4:
Find Solution using Least Cost method
D1 D2 D3 D4 Supply
S1 19 30 50 10 7
S2 70 30 40 60 9
S3 40 8 70 20 18
Demand 5 8 7 14 34/34
Step-1. Identify Least Cost value Out of all Cost values…
Here 8 Rs. is least Cost
Step2. Do First allocation in this S3-D2 cell
D2 demand 8 is less than S3 supply 18, so allocate 8
Now no need to consider D2 column value further.
D1 D2 D3 D4 Supply
S1 19 30 50 10 7
S2 70 30 40 60 9
S3 40 8 (8) 70 20 18
Demand 5 8 7 14
Step 3: Identify next to smallest cost value that is 10 Rs.
Step 4: Do allocate in S1-D4 Cell.
S1 Supply 7 is less than D4 Demand 14 so allocate 7
Now no need to consider S1 row value further.
D1 D2 D3 D4 Supply
S1 19 30 50 10 (7) 7
S2 70 30 40 60 9
S3 40 8 (8) 70 20 18
Demand 5 8 7 14
Follow similar steps.
Next smallest cost value is 20 (As we have no need to
consider S1 row values).
Possible Allocation in S3-D4 cell is 7
D1 D2 D3 D4 Supply
S1 19 30 50 10 (7) 7
S2 70 30 40 60 9
S3 40 8 (8) 70 20 (7) 18
Demand 5 8 7 14
Here, next two cost 40 Rs. are same in two cell .
It is Situation of tie.
Do allocate where maximum allocation possible that is in cell S2-D3.
Allocate 7 , as demand in D3 is 7 which is less than supply in S2, 9.
D1 D2 D3 D4 Supply
S1 19 30 50 10 (7) 7
S2 70 30 40 (7) 60 9
S3 40 8 (8) 70 20 (7) 18
Demand 5 8 7 14
Next allocation is in S3-D1 that is 18-8-7=3
D1 D2 D3 D4 Supply
S1 19 30 50 10 (7) 7
S2 70 30 40 (7) 60 9
S3 40 (3) 8 (8) 70 20 (7) 18
Demand 5 8 7 14
Next allocation is in S2-D1 that is 9-7= 5-3 =2
D1 D2 D3 D4 Supply
S1 19 30 50 10 (7) 7
S2 70 (2) 30 40 (7) 60 9
S3 40 (3) 8 (8) 70 20 (7) 18
Demand 5 8 7 14
The minimum total transportation cost =
(10×7)+(70×2)+(40×7)+(40×3)+(8×8)+(20×7) = 814 Rs.
Here,
m=total rows=3
n=total columns=4
the number of allocated cells = 6
is equal to
m + n - 1 = 3 + 4 - 1 = 6
∴ This solution is non-degenerate
Example 5: LCM Method- Practice Problem
D1 D2 D3 D4 Supply
S1 11 13 17 14 250
S2 16 18 14 10 300
S3 21 24 13 10 (250) 400
Demand 200 225 275 250
D1 D2 D3 D4 Supply
S1 11 (200) 13 17 14 250
S2 16 18 14 10 300
S3 21 24 13 10 (250) 400
Demand 200 225 275 250
D1 D2 D3 D4 Supply
S1 11 (200) 13 (50) 17 14 250
S2 16 18 14 10 300
S3 21 24 13 10 (250) 400
Demand 200 225 275 250
D1 D2 D3 D4 Supply
S1 11 (200) 13 (50) 17 14 250
S2 16 18 14 10 300
S3 21 24 13 (150) 10 (250) 400
Demand 200 225 275 250
D1 D2 D3 D4 Supply
S1 11 (200) 13 (50) 17 14 250
S2 16 18 14 (125) 10 300
S3 21 24 13 (150) 10 (250) 400
Demand 200 225 275 250
D1 D2 D3 D4 Supply
S1 11 (200) 13 (50) 17 14 250
S2 16 18 (175) 14 (125) 10 300
S3 21 24 13 (150) 10 (250) 400
Demand 200 225 275 250
The minimum total transportation cost =
11*200 + 13*50 + 18*175 + 14*125 + 13*150 + 10*250
= 12200 Rs.
Here,
the number of allocated cells = 6
is equal to
m + n - 1 = 3 + 4 - 1 = 6
∴ This solution is non-degenerate
Example 6:
Solve example using Vogel’s Approximation Method (VAM Method)
D1 D2 D3 D4 Supply
S1 19 30 50 10 7
S2 70 30 40 60 9
S3 40 8 70 20 18
Demand 5 8 7 14
D1 D2 D3 D4 Supply
Row
Difference
S1 19 30 50 10 7 9=19-10
S2 70 30 40 60 9 10=40-30
S3 40 8 70 20 18 12=20-8
Demand 5 8 7 14
Column
difference
21=40-19 22=30-8 10=50-40 10=20-10
D1 D2 D3 D4 Supply
Row
Differences
S1 19 30 50 10 7 9
S2 70 30 40 60 9 10
S3 40 8(8) 70 20 18 12
Demand 5 8 7 14 34/34
Column
Differences
21 22 10 10
D1 D2 D3 D4 Supply
Row
Differences
S1 19(5) 30 50 10 7 9 9
S2 70 30 40 60 9 10 20
S3 40 8(8) 70 20 18 12 20
Demand 5 8 7 14 34/34
Column
Differences
21
21
22
--
10
10
10
10
D1 D2 D3 D4 Supply Row
Differences
S1 19(5) 30 50 10 7 9 9 40
S2 70 30 40 60 9 10 20 20
S3 40 8(8) 70 20(10) 18 12 20 50
Demand 5 8 7 14 34/34
Column
Differences
21
21
--
22
--
--
10
10
10
10
10
10
D1 D2 D3 D4 Supply Row
Differences
S1 19(5) 30 50 10(2) 7 9 9 40 40
S2 70 30 40 60 9 10 20 20 20
S3 40 8(8) 70 20(10) 18 12 20 50 -
Demand 5 8 7 14 34/34
Column
Differences
21
21
--
--
22
--
--
--
10
10
10
10
10
10
10
50
D1 D2 D3 D4 Supply Row
Differences
S1 19(5) 30 50 10(2) 7 9 9 40 40 -
S2 70 30 40 60(2) 9 10 20 20 20 20
S3 40 8(8) 70 20(10) 18 12 20 50 - -
Demand 5 8 7 14 34/34
Column
Differences
21
21
--
--
--
22
--
--
--
--
10
10
10
10
40
10
10
10
50
60
D1 D2 D3 D4 Supply Row
Differences
S1 19(5) 30 50 10(2) 7 9 9 40 40 - -
S2 70 30 40(7) 60(2) 9 10 20 20 20 20 40
S3 40 8(8) 70 20(10) 18 12 20 50 - - -
Demand 5 8 7 14 34/34
Column
Differences
21
21
--
--
--
--
22
--
--
--
--
--
10
10
10
10
40
40
10
10
10
50
60
--
The minimum total transportation cost =
19×5 + 10×2 + 40×7 + 60×2 + 8×8 + 20×10 = 779 Rs.
Here, the number of allocated cells = 6 is equal to
m + n - 1 = 3 + 4 - 1 = 6
∴ This solution is non-degenerate
Example 7
Find Solution using Vogel's Approximation method
D1 D2 D3 D4 Supply
S1 11 13 17 14 250
S2 16 18 14 10 300
S3 21 24 13 10 400
Demand 200 225 275 250
D1
D2 D3 D4 Supply
Row
Differences
S1 11(200) 13 17 14 250 2 - ------
S2 16 18 14 10 300 4 -----
S3 21 24 13 10 400 3 -
Demand 200 225 275 250
Column
Differenc
es
5
--
--
5
--
1
0
D1
D2 D3 D4 Supply Row Differences
S1 11(200) 13(50) 17 14 250 2 1--- ------
S2 16 18 14 10 300 4 4-- -------
S3 21 24 13 10 400 3 3--
Deman
d
200 225 275 250
Column
Differen
ces
5
--
--
--
5
5
--
1
1
0
0
0
0
D1
D2 D3 D4 Supply Row Differences
S1 11(200) 13(50) 17 14 250 2 1--- ------
S2 16 18(175) 14 10 300 4 4--4
S3 21 24 13 10 400 3 3--3
Demand 200 225 275 250
Column
Differenc
es
5
--
--
--
--
--
5
5
6
--
--
--
1
1
1
--
0
0
0
0
D1
D2 D3 D4 Supply Row Differences
S1 11(200) 13(50) 17 14 250 2 1--- ------
S2 16 18(175) 14 10(125) 300 4 4--4 4-------
S3 21 24 13 10 400 3 3--3 3-
Demand 200 225 275 250
Column
Differenc
es
5
--
--
--
--
--
5
5
6
--
--
--
1
1
1
1
--
0
0
0
0
D1
D2 D3 D4 Supply Row Differences
S1 11(200) 13(50) 17 14 250 2 1--- ------
S2 16 18(175) 14 10(125) 300 4 4--4 4-------
S3 21 24 13(275) 10 400 3 3--3 3-3-
Demand 200 225 275 250
Column
Differenc
es
5
--
--
--
--
--
5
5
6
--
--
--
1
1
1
1
13
--
0
0
0
0
10
D1
D2 D3 D4 Supply Row Differences
S1 11(200) 13(50) 17 14 250 2 1--- ------
S2 16 18(175) 14 10(125) 300 4 4--4 4-------
S3 21 24 13(275) 10(125) 400 3 3--3 3-3-10
Demand 200 225 275 250
Column
Differenc
es
5
--
--
--
--
--
5
5
6
--
--
--
1
1
1
1
13
--
0
0
0
0
10
10
D1 D2 D3 D4 Supply Row Differences
S1 11(200) 13(50) 17 14 250 2 | 1 | -- | -- | -- | -- |
S2 16 18(175) 14 10(125) 300 4 | 4 | 4 | 4 | -- | -- |
S3 21 24 13(275) 10(125) 400 3 | 3 | 3 | 3 | 3 | 10 |
Demand 200 225 275 250
Column
Differences
5
--
--
--
--
--
5
5
6
--
--
--
1
1
1
1
13
--
0
0
0
0
10
10
The minimum total transportation cost
=11×200+13×50+18×175+10×125+13×275+10×125
=12075
Here, the number of allocated cells = 6 is equal to
m + n - 1 = 3 + 4 - 1 = 6
∴ This solution is non-degenerate
Optimality Test
Question–Modified Distribution Method --MODI Method Steps
(Rule) ---7 Marks
Step-1:Find an initial basic feasible solution--IBFS--using any
one of the three methods NWCM, LCM or VAM.
Step-2:Find ui and vj for rows and columns.
To start
a. assign 0 to ui or vj where maximum number of allocation in
a row or column respectively.
b. Calculate other ui's and vj's using cij=ui+vj, for all occupied
cells.
Step-3:
For all unoccupied cells (i , j),
calculate dij=cij-(ui+vj)
Step-4:Check the sign of dij
a. If dij>0, then current basic feasible solution is optimal and stop
this procedure.
b. If dij=0 then alternative solution exists, with different set
allocation and same transportation cost.
C. If dij<0, then the given solution is not an optimal solution and
further improvement in the solution is possible.
Step-5:Select the unoccupied cell with the largest negative value of
dij
Step-6:Draw a closed path (or loop) from the unoccupied cell
(selected in the previous step).
Mark (+) and (-) sign alternatively at each corner, starting from
the original unoccupied cell.
Step-7: Repeat Step-2 to step-7 until optimal solution is
obtained.
This procedure stops when all dij≥0 for unoccupied cells
Example 7: Find optimal solution using MODI Method
D1 D2 D3 D4 Supply
S1 19 30 50 10 7
S2 70 30 40 60 9
S3 40 8 70 20 18
Demand 5 8 7 14
D1 D2 D3 D4 Supply
S1 19(5) 30 50 10(2) 7
S2 70 30 40(7) 60(2) 9
S3 40 8(8) 70 20(10) 18
Demand 5 8 7 14 34/34
Step 1: Find solution using VAM method
Step-2:Find ui and vj for rows and columns.
To start
a. assign 0 to ui or vj where maximum number of allocation in a
row or column respectively.
b. Calculate other ui's and vj's using cij=ui+vj, for all occupied cells.
D1 D2 D3 D4 Supply
S1 19(5) 30 50 10(2) 7 u1=
S2 70 30 40(7) 60(2) 9 u2=
S3 40 8(8) 70 20(10) 18 u3=
Demand 5 8 7 14 34/34
V1= V2= V3= v4= 0
Iteration-1 of optimality test
Find ui and vj for all occupied cells(i , j), where cij=ui+vj= cost from
i row to j column
1. Substituting, v4=0, we get
2.c14=u1+v4⇒u1=c14-v4⇒u1=10-0⇒u1=10
3.c11=u1+v1⇒v1=c11-u1⇒v1=19-10⇒v1=9
D1 D2 D3 D4 Supply
S1 19(5) 30 50 10(2) 7 u1= 10
S2 70 30 40(7) 60(2) 9 u2=
S3 40 8(8) 70 20(10) 18 u3=
Demand 5 8 7 14 34/34
v1= 9 v2= v3= v4= 0
4.c24=u2+v4⇒u2=c24-v4⇒u2=60-0⇒u2=60
5.c23=u2+v3⇒v3=c23-u2⇒v3=40-60⇒v3=-20
6.c34=u3+v4⇒u3=c34-v4⇒u3=20-0⇒u3=20
7.c32=u3+v2⇒v2=c32-u3⇒v2=8-20⇒v2=-12
D1 D2 D3 D4 Supply
S1 19(5) 30 50 10(2) 7 u1= 10
S2 70 30 40(7) 60(2) 9 u2= 60
S3 40 8(8) 70 20(10) 18 u3= 20
Demand 5 8 7 14 34/34
v1= 9 v2= -12 v3= -20 v4= 0
Step-3:
For all unoccupied cells (i,j),
calculate dij=cij-(ui+vj)
1.d12=c12-(u1+v2)=30-(10-12)=32
2.d13=c13-(u1+v3)=50-(10-20)=60
3.d21=c21-(u2+v1)=70-(60+9)=1
4.d22=c22-(u2+v2)=30-(60-12)=-18
5.d31=c31-(u3+v1)=40-(20+9)=11
6.d33=c33-(u3+v3)=70-(20-20)=70
D1 D2 D3 D4 Supply
S1 19(5) 30 [32] 50 [60] 10(2) 7 u1= 10
S2 70 [1] 30 [-18] 40(7) 60(2) 9 u2= 60
S3 40 [11] 8(8) 70 [70] 20(10) 18 u3= 20
Demand 5 8 7 14 34/34
v1= 9 v2= -12 v3= -20 v4= 0
Step-4:Check the sign of dij
a. If dij>0, then current basic feasible solution is optimal and
stop this procedure.
b. If dij=0 then alternative solution exists, with different set
allocation and same transportation cost.
C. If dij<0, then the given solution is not an optimal solution and
further improvement in the solution is possible.
Here d22= -18 which is less than zero,
so it is non optimal solution
Step-5:Select the unoccupied cell with the largest negative
value of dij
Step-6:Draw a closed path (or loop) from the unoccupied cell
(selected in the previous step).
Mark (+) and (-) sign alternatively at each corner, starting from
the original unoccupied cell.
Now choose the minimum negative value from all dij
(opportunity cost) = d22 = [-18]
and draw a closed path from S2D2.
Closed path is S2D2→S2D4→S3D4→S3D2
Closed path loop and plus/minus sign allocation…
1. Select the minimum value from cells marked with (-) sign of the
closed path.
2. Assign this value to selected unoccupied cell (So unoccupied cell
becomes occupied
3. Add this value to the other occupied cells marked with (+) sign.
4. Subtract this value to the other occupied cells marked with (-)
sign.
D1 D2 D3 D4 Supply
S1 19(5) 30 [32] 50 [60] 10(2) 7 u1= 10
S2 70 [1] 30 [-18] + 40(7) 60(2) - 9 u2= 60
S3 40 [11] 8(8) - 70 [70] 20(10) + 18 u3= 20
Demand 5 8 7 14 34/34
v1= 9 v2= -12 v3= -20 v4= 0
D1 D2 D3 D4 Supply
S1 19(5) 30 50 10(2) 7
S2 70 30(2) 40(7) 60 9
S3 40 8(6) 70 20(12) 18
Step-7: Repeat Step-2 to step-7 until optimal solution is
obtained.
This procedure stops when all dij≥0 for unoccupied cells
D1 D2 D3 D4 Supply ui
S1 19 (5) 30 [32] 50 [42] 10 (2) 7 u1=0
S2 70 [19] 30 (2) 40 (7) 60 [18] 9 u2=32
S3 40 [11] 8 (6) 70 [52] 20 (12) 18 u3=10
Demand 5 8 7 14
vj v1=19 v2=-2 v3=8 v4=10
Since all dij≥0.
So final optimal solution is arrived.
D1 D2 D3 D4 Supply
S1 19(5) 30 50 10(2) 7
S2 70 30(2) 40(7) 60 9
S3 40 8(6) 70 20(12) 18
The minimum total transportation cost
= 19×5 + 10×2 + 30×2 + 40×7 + 8×6 + 20×12
= 743
Variations in Transportation
1. Unbalance Supply and Demand
2. Degeneracy and its resolution
3. Maximization Problem
1. Unbalance Supply and Demand
Solution : Add dummy row or column
Supply less  Add Dummy Row
Demand less  Add Dummy Column
D1 D2 D3 Supply
S1 5 4 7 120
S2 10 15 12 80
S3 3 5 12 60
Demand 150 80 50 280/260
Unbalance Supply and Demand
Here, Total supply = 260
Total Demand = 280
Add dummy row
Solution : Supply 260 is less than demand 280,
D1 D2 D3 Supply
S1 5 4 7 120
S2 10 15 12 80
S3 3 5 12 60
Sdummy 0 0 0 20
Demand 150 80 50 280/280
Now, Total supply = Total Demand = 280,
So it is balanced Problem,
Now we can find IBFS using NWCM, LCM Or VAM Method.
Supply less  Add Dummy Row
D1 D2 D3 Supply
S1 5 4 7 100
S2 10 15 12 100
S3 3 5 12 50
Demand 80 80 50 210/250
Unbalance Supply and Demand
Here, Total supply = 250
Total Demand = 210
Solution : Demand 210 is less than supply 250,
Add dummy column
D1 D2 D3 Ddummy Supply
S1 5 4 7 0 100
S2 10 15 12 0 100
S3 3 5 12 0 50
Demand 80 80 50 40 250/250
Now, Total supply = Total Demand = 250,
So it is balanced Problem,
Now we can find IBFS using NWCM, LCM Or VAM Method.
Demand less  Add Dummy Column
2. Degeneracy and its resolution
(Convert Degenerate solution into non degenerate solution)
Solution :
• To resolve degeneracy, we make use of an artificial quantity
delta (Δ )
• The quantity Δ is assigned to that unoccupied cell, which
has the minimum transportation cost.
D1 D2 D3 Supply
S1 8(70) 5 6(50) 120
S2 15 10(80) 12 80
S3 3(80) 9 10 80
Demand 150 80 50 280/280
Initial feasible solution by VAM method is
Here, the number of allocated cells = 4,
which is one less than m + n - 1 = 3 + 3 - 1 = 5
∴ This solution is degenerate
Here, the number of allocated cells = 4,
which is one less than m + n - 1 = 3 + 3 - 1 = 5
∴ This solution is degenerate
To Make it Non degenerate,
The quantity Δ is assigned to S1D2, which has the
minimum transportation cost = 5.
D1 D2 D3 Supply
S1 8(70) 5 (Δ) 6(50) 120
S2 15 10(80) 12 80
S3 3(80) 9 10 80
Demand 150 80 50 280/280
Here, Now Number of allocated cell = 5 And
m+n-1=5,
Now, Solution is non degenerate.
Now we can do optimality Test
Minimum transportation cost = 5 Rs. Here Assign (Δ) in this (S1, D2) cell
3. Maximization Problem
Solution: Convert into Minimization Problem
How ?? :: By subtracting all cost values from maximum
cost value.
----Than apply LCM, NWCM Or VAM Method
In data it is mentioned-Find maximum profit .
D1 D2 D3 D4 Supply
S1 10 20 30 20 7
S2 30 10 40 60 9
S3 40 50 70 20 18
Demand 5 8 7 14
10, 20, 30, 20…etc are profit values.
Convert into Minimization problem subtracting all values from
maximum value (70 Rs).
Convert into Minimization problem subtracting all values from
maximum value (70 Rs).
Updated New Table is below,
D1 D2 D3 D4 Supply
S1 60 50 40 50 7
S2 40 60 30 10 9
S3 30 20 0 50 18
Demand 5 8 7 14
Now find IBFS using NWCM, LCM or VAM Method.
Summery Of Transportation Chapter
 1. Find Initial Basic Feasible Solution-IBFS Using
a) North West Corner Method--NWCM ,
b) Least Cost Method--LCM and
c) Vogel’s Approximation Method--VAM
 2. Optimality Test using Modified Distribution Method-
MODI method.
 3. Variation in transportation
a) Unbalance Supply and Demand
b) Degeneracy and its resolution
c) Maximization Problem

More Related Content

What's hot

Transportation problem
Transportation problemTransportation problem
Transportation problemA B
 
Optimal Solution by MODI Method
Optimal Solution by MODI MethodOptimal Solution by MODI Method
Optimal Solution by MODI Method
DrDeepaChauhan
 
Assignment problem
Assignment problemAssignment problem
Assignment problemAbu Bashar
 
Transportation Problem
Transportation ProblemTransportation Problem
Transportation Problem
Alvin Niere
 
Transportation and transshipment problems
Transportation  and transshipment problemsTransportation  and transshipment problems
Transportation and transshipment problems
Dr. Adinath Damale
 
North West Corner Rule
North   West Corner RuleNorth   West Corner Rule
North West Corner Ruleitsvineeth209
 
ITFT - Assignment problem
ITFT - Assignment problemITFT - Assignment problem
ITFT - Assignment problem
JasmineKaur29
 
Vogel’s Approximation Method (VAM)
Vogel’s Approximation Method (VAM)Vogel’s Approximation Method (VAM)
Vogel’s Approximation Method (VAM)
dkpawar
 
transporation problem - stepping stone method
transporation problem - stepping stone methodtransporation problem - stepping stone method
transporation problem - stepping stone method
oragon291764
 
PERT
PERTPERT
Transportation model
Transportation modelTransportation model
Transportation model
Lokesh Payasi
 
LEAST COST METHOD
LEAST COST METHOD LEAST COST METHOD
LEAST COST METHOD
VishalHotchandani2
 
primal and dual problem
primal and dual problemprimal and dual problem
primal and dual problem
Yash Lad
 
5. transportation problems
5. transportation problems5. transportation problems
5. transportation problems
Hakeem-Ur- Rehman
 
North west corner method
North west corner method North west corner method
North west corner method
Akash Jadhav
 
Transportation Modelling - Quantitative Analysis and Discrete Maths
Transportation Modelling - Quantitative Analysis and Discrete MathsTransportation Modelling - Quantitative Analysis and Discrete Maths
Transportation Modelling - Quantitative Analysis and Discrete MathsKrupesh Shah
 
Simplex method: Slack, Surplus & Artificial variable
Simplex method:  Slack, Surplus & Artificial variableSimplex method:  Slack, Surplus & Artificial variable
Simplex method: Slack, Surplus & Artificial variable
DevyaneeDevyanee2007
 
Pert and CPM
Pert and CPMPert and CPM
Pert and CPM
Sachin Kapoor
 

What's hot (20)

Transportation problem
Transportation problemTransportation problem
Transportation problem
 
Optimal Solution by MODI Method
Optimal Solution by MODI MethodOptimal Solution by MODI Method
Optimal Solution by MODI Method
 
Vam
VamVam
Vam
 
Assignment problem
Assignment problemAssignment problem
Assignment problem
 
Transportation Problem
Transportation ProblemTransportation Problem
Transportation Problem
 
Transportation and transshipment problems
Transportation  and transshipment problemsTransportation  and transshipment problems
Transportation and transshipment problems
 
North West Corner Rule
North   West Corner RuleNorth   West Corner Rule
North West Corner Rule
 
ITFT - Assignment problem
ITFT - Assignment problemITFT - Assignment problem
ITFT - Assignment problem
 
Vogel’s Approximation Method (VAM)
Vogel’s Approximation Method (VAM)Vogel’s Approximation Method (VAM)
Vogel’s Approximation Method (VAM)
 
Assignment problem
Assignment problemAssignment problem
Assignment problem
 
transporation problem - stepping stone method
transporation problem - stepping stone methodtransporation problem - stepping stone method
transporation problem - stepping stone method
 
PERT
PERTPERT
PERT
 
Transportation model
Transportation modelTransportation model
Transportation model
 
LEAST COST METHOD
LEAST COST METHOD LEAST COST METHOD
LEAST COST METHOD
 
primal and dual problem
primal and dual problemprimal and dual problem
primal and dual problem
 
5. transportation problems
5. transportation problems5. transportation problems
5. transportation problems
 
North west corner method
North west corner method North west corner method
North west corner method
 
Transportation Modelling - Quantitative Analysis and Discrete Maths
Transportation Modelling - Quantitative Analysis and Discrete MathsTransportation Modelling - Quantitative Analysis and Discrete Maths
Transportation Modelling - Quantitative Analysis and Discrete Maths
 
Simplex method: Slack, Surplus & Artificial variable
Simplex method:  Slack, Surplus & Artificial variableSimplex method:  Slack, Surplus & Artificial variable
Simplex method: Slack, Surplus & Artificial variable
 
Pert and CPM
Pert and CPMPert and CPM
Pert and CPM
 

Similar to Transportation Method Operation Research

transportationoperationresearch-210111101338.pptx
transportationoperationresearch-210111101338.pptxtransportationoperationresearch-210111101338.pptx
transportationoperationresearch-210111101338.pptx
ProfessionalDeeksha
 
VAM and MODI Method in Solving Transportation Problems
VAM and MODI Method in Solving Transportation ProblemsVAM and MODI Method in Solving Transportation Problems
VAM and MODI Method in Solving Transportation Problems
Karlo Maniego
 
North West Corner Method
North West Corner MethodNorth West Corner Method
North West Corner Method
UsharaniRavikumar
 
Operation Research Lectures about research
Operation Research Lectures about researchOperation Research Lectures about research
Operation Research Lectures about research
RITHMETIC
 
Vogel's Approximation Method
Vogel's Approximation MethodVogel's Approximation Method
Vogel's Approximation Method
UsharaniRavikumar
 
Transportation Problem
Transportation ProblemTransportation Problem
Transportation Problem
VivekSaurabh7
 
VOGEL'S APPROXIMATION METHOD
VOGEL'S APPROXIMATION METHODVOGEL'S APPROXIMATION METHOD
VOGEL'S APPROXIMATION METHOD
SwethaShree13
 
unit2 linear programming problem in .pdf
unit2 linear programming problem in .pdfunit2 linear programming problem in .pdf
unit2 linear programming problem in .pdf
bizuayehuadmasu1
 
unit-5 Transportation problem in operation research ppt.pdf
unit-5 Transportation problem in operation research ppt.pdfunit-5 Transportation problem in operation research ppt.pdf
unit-5 Transportation problem in operation research ppt.pdf
bizuayehuadmasu1
 
Unit.5. transportation and assignment problems
Unit.5. transportation and assignment problemsUnit.5. transportation and assignment problems
Unit.5. transportation and assignment problems
DagnaygebawGoshme
 
OR CH 3 Transportation and assignment problem.pptx
OR CH 3 Transportation and assignment problem.pptxOR CH 3 Transportation and assignment problem.pptx
OR CH 3 Transportation and assignment problem.pptx
AbdiMuceeTube
 
Lecture 7 transportation problem finding initial basic feasible solution
Lecture 7 transportation problem finding initial basic feasible solutionLecture 7 transportation problem finding initial basic feasible solution
Lecture 7 transportation problem finding initial basic feasible solution
Aathi Suku
 
OR PPT.pdf
OR PPT.pdfOR PPT.pdf
OR PPT.pdf
KULDEEPSINGH637195
 
Transportation Problem- Initial Basic Feasible Solution
Transportation Problem- Initial Basic Feasible SolutionTransportation Problem- Initial Basic Feasible Solution
Transportation Problem- Initial Basic Feasible Solution
DrDeepaChauhan
 
Lecture (3) _transportation problem31-10-2020.pdf
Lecture (3) _transportation problem31-10-2020.pdfLecture (3) _transportation problem31-10-2020.pdf
Lecture (3) _transportation problem31-10-2020.pdf
amrhebafamily
 
Maths Saves Money
Maths Saves MoneyMaths Saves Money
Maths Saves Money
Kartik918
 
Filter design and simulation
Filter design and simulationFilter design and simulation
Filter design and simulation
Sandesh Agrawal
 
STAQ based Matrix estimation - initial concept (presented at hEART conference...
STAQ based Matrix estimation - initial concept (presented at hEART conference...STAQ based Matrix estimation - initial concept (presented at hEART conference...
STAQ based Matrix estimation - initial concept (presented at hEART conference...
Luuk Brederode
 
Operations Research Modeling Toolset
Operations Research Modeling ToolsetOperations Research Modeling Toolset
Operations Research Modeling Toolset
FellowBuddy.com
 
Transporataion method north waste corner
Transporataion method north waste cornerTransporataion method north waste corner
Transporataion method north waste corner
SmitaSonawane7
 

Similar to Transportation Method Operation Research (20)

transportationoperationresearch-210111101338.pptx
transportationoperationresearch-210111101338.pptxtransportationoperationresearch-210111101338.pptx
transportationoperationresearch-210111101338.pptx
 
VAM and MODI Method in Solving Transportation Problems
VAM and MODI Method in Solving Transportation ProblemsVAM and MODI Method in Solving Transportation Problems
VAM and MODI Method in Solving Transportation Problems
 
North West Corner Method
North West Corner MethodNorth West Corner Method
North West Corner Method
 
Operation Research Lectures about research
Operation Research Lectures about researchOperation Research Lectures about research
Operation Research Lectures about research
 
Vogel's Approximation Method
Vogel's Approximation MethodVogel's Approximation Method
Vogel's Approximation Method
 
Transportation Problem
Transportation ProblemTransportation Problem
Transportation Problem
 
VOGEL'S APPROXIMATION METHOD
VOGEL'S APPROXIMATION METHODVOGEL'S APPROXIMATION METHOD
VOGEL'S APPROXIMATION METHOD
 
unit2 linear programming problem in .pdf
unit2 linear programming problem in .pdfunit2 linear programming problem in .pdf
unit2 linear programming problem in .pdf
 
unit-5 Transportation problem in operation research ppt.pdf
unit-5 Transportation problem in operation research ppt.pdfunit-5 Transportation problem in operation research ppt.pdf
unit-5 Transportation problem in operation research ppt.pdf
 
Unit.5. transportation and assignment problems
Unit.5. transportation and assignment problemsUnit.5. transportation and assignment problems
Unit.5. transportation and assignment problems
 
OR CH 3 Transportation and assignment problem.pptx
OR CH 3 Transportation and assignment problem.pptxOR CH 3 Transportation and assignment problem.pptx
OR CH 3 Transportation and assignment problem.pptx
 
Lecture 7 transportation problem finding initial basic feasible solution
Lecture 7 transportation problem finding initial basic feasible solutionLecture 7 transportation problem finding initial basic feasible solution
Lecture 7 transportation problem finding initial basic feasible solution
 
OR PPT.pdf
OR PPT.pdfOR PPT.pdf
OR PPT.pdf
 
Transportation Problem- Initial Basic Feasible Solution
Transportation Problem- Initial Basic Feasible SolutionTransportation Problem- Initial Basic Feasible Solution
Transportation Problem- Initial Basic Feasible Solution
 
Lecture (3) _transportation problem31-10-2020.pdf
Lecture (3) _transportation problem31-10-2020.pdfLecture (3) _transportation problem31-10-2020.pdf
Lecture (3) _transportation problem31-10-2020.pdf
 
Maths Saves Money
Maths Saves MoneyMaths Saves Money
Maths Saves Money
 
Filter design and simulation
Filter design and simulationFilter design and simulation
Filter design and simulation
 
STAQ based Matrix estimation - initial concept (presented at hEART conference...
STAQ based Matrix estimation - initial concept (presented at hEART conference...STAQ based Matrix estimation - initial concept (presented at hEART conference...
STAQ based Matrix estimation - initial concept (presented at hEART conference...
 
Operations Research Modeling Toolset
Operations Research Modeling ToolsetOperations Research Modeling Toolset
Operations Research Modeling Toolset
 
Transporataion method north waste corner
Transporataion method north waste cornerTransporataion method north waste corner
Transporataion method north waste corner
 

More from R A Shah

Buoyancy and flotation _ forces on immersed body
Buoyancy and flotation _ forces on immersed bodyBuoyancy and flotation _ forces on immersed body
Buoyancy and flotation _ forces on immersed body
R A Shah
 
Plain scale and Diagonal Scale Engineering Graphics
Plain scale and Diagonal Scale Engineering GraphicsPlain scale and Diagonal Scale Engineering Graphics
Plain scale and Diagonal Scale Engineering Graphics
R A Shah
 
Dimensional analysis Similarity laws Model laws
Dimensional analysis Similarity laws Model laws Dimensional analysis Similarity laws Model laws
Dimensional analysis Similarity laws Model laws
R A Shah
 
Engineering Graphics Laboratory manual
Engineering Graphics Laboratory manualEngineering Graphics Laboratory manual
Engineering Graphics Laboratory manual
R A Shah
 
Governor
GovernorGovernor
Governor
R A Shah
 
Diagonal scale
Diagonal scaleDiagonal scale
Diagonal scale
R A Shah
 
Synthesis of Mechanism
Synthesis of MechanismSynthesis of Mechanism
Synthesis of Mechanism
R A Shah
 
Kinematics of Machine study material
Kinematics of Machine study material Kinematics of Machine study material
Kinematics of Machine study material
R A Shah
 
Game Theory Operation Research
Game Theory Operation ResearchGame Theory Operation Research
Game Theory Operation Research
R A Shah
 
Construct Parabola Hyperbola Engineering Graphics
Construct Parabola Hyperbola Engineering GraphicsConstruct Parabola Hyperbola Engineering Graphics
Construct Parabola Hyperbola Engineering Graphics
R A Shah
 
Construct Ellipse Engineering Graphics
Construct Ellipse Engineering GraphicsConstruct Ellipse Engineering Graphics
Construct Ellipse Engineering Graphics
R A Shah
 
Dimensioning System Engineering Graphics
Dimensioning System Engineering GraphicsDimensioning System Engineering Graphics
Dimensioning System Engineering Graphics
R A Shah
 
Plain scale Engineering Graphics
Plain scale Engineering GraphicsPlain scale Engineering Graphics
Plain scale Engineering Graphics
R A Shah
 
Inversion of mechanism
Inversion of mechanismInversion of mechanism
Inversion of mechanism
R A Shah
 
Replacement theory
Replacement theoryReplacement theory
Replacement theory
R A Shah
 
Inventory control
Inventory controlInventory control
Inventory control
R A Shah
 
Cam and follower
Cam and followerCam and follower
Cam and follower
R A Shah
 
Mechanism and machines, Inversion, Link pair chain, Kinematics of machine, de...
Mechanism and machines, Inversion, Link pair chain, Kinematics of machine, de...Mechanism and machines, Inversion, Link pair chain, Kinematics of machine, de...
Mechanism and machines, Inversion, Link pair chain, Kinematics of machine, de...
R A Shah
 

More from R A Shah (18)

Buoyancy and flotation _ forces on immersed body
Buoyancy and flotation _ forces on immersed bodyBuoyancy and flotation _ forces on immersed body
Buoyancy and flotation _ forces on immersed body
 
Plain scale and Diagonal Scale Engineering Graphics
Plain scale and Diagonal Scale Engineering GraphicsPlain scale and Diagonal Scale Engineering Graphics
Plain scale and Diagonal Scale Engineering Graphics
 
Dimensional analysis Similarity laws Model laws
Dimensional analysis Similarity laws Model laws Dimensional analysis Similarity laws Model laws
Dimensional analysis Similarity laws Model laws
 
Engineering Graphics Laboratory manual
Engineering Graphics Laboratory manualEngineering Graphics Laboratory manual
Engineering Graphics Laboratory manual
 
Governor
GovernorGovernor
Governor
 
Diagonal scale
Diagonal scaleDiagonal scale
Diagonal scale
 
Synthesis of Mechanism
Synthesis of MechanismSynthesis of Mechanism
Synthesis of Mechanism
 
Kinematics of Machine study material
Kinematics of Machine study material Kinematics of Machine study material
Kinematics of Machine study material
 
Game Theory Operation Research
Game Theory Operation ResearchGame Theory Operation Research
Game Theory Operation Research
 
Construct Parabola Hyperbola Engineering Graphics
Construct Parabola Hyperbola Engineering GraphicsConstruct Parabola Hyperbola Engineering Graphics
Construct Parabola Hyperbola Engineering Graphics
 
Construct Ellipse Engineering Graphics
Construct Ellipse Engineering GraphicsConstruct Ellipse Engineering Graphics
Construct Ellipse Engineering Graphics
 
Dimensioning System Engineering Graphics
Dimensioning System Engineering GraphicsDimensioning System Engineering Graphics
Dimensioning System Engineering Graphics
 
Plain scale Engineering Graphics
Plain scale Engineering GraphicsPlain scale Engineering Graphics
Plain scale Engineering Graphics
 
Inversion of mechanism
Inversion of mechanismInversion of mechanism
Inversion of mechanism
 
Replacement theory
Replacement theoryReplacement theory
Replacement theory
 
Inventory control
Inventory controlInventory control
Inventory control
 
Cam and follower
Cam and followerCam and follower
Cam and follower
 
Mechanism and machines, Inversion, Link pair chain, Kinematics of machine, de...
Mechanism and machines, Inversion, Link pair chain, Kinematics of machine, de...Mechanism and machines, Inversion, Link pair chain, Kinematics of machine, de...
Mechanism and machines, Inversion, Link pair chain, Kinematics of machine, de...
 

Recently uploaded

Azure Interview Questions and Answers PDF By ScholarHat
Azure Interview Questions and Answers PDF By ScholarHatAzure Interview Questions and Answers PDF By ScholarHat
Azure Interview Questions and Answers PDF By ScholarHat
Scholarhat
 
Reflective and Evaluative Practice...pdf
Reflective and Evaluative Practice...pdfReflective and Evaluative Practice...pdf
Reflective and Evaluative Practice...pdf
amberjdewit93
 
How to Build a Module in Odoo 17 Using the Scaffold Method
How to Build a Module in Odoo 17 Using the Scaffold MethodHow to Build a Module in Odoo 17 Using the Scaffold Method
How to Build a Module in Odoo 17 Using the Scaffold Method
Celine George
 
The basics of sentences session 5pptx.pptx
The basics of sentences session 5pptx.pptxThe basics of sentences session 5pptx.pptx
The basics of sentences session 5pptx.pptx
heathfieldcps1
 
Introduction to AI for Nonprofits with Tapp Network
Introduction to AI for Nonprofits with Tapp NetworkIntroduction to AI for Nonprofits with Tapp Network
Introduction to AI for Nonprofits with Tapp Network
TechSoup
 
Fresher’s Quiz 2023 at GMC Nizamabad.pptx
Fresher’s Quiz 2023 at GMC Nizamabad.pptxFresher’s Quiz 2023 at GMC Nizamabad.pptx
Fresher’s Quiz 2023 at GMC Nizamabad.pptx
SriSurya50
 
How to Add Chatter in the odoo 17 ERP Module
How to Add Chatter in the odoo 17 ERP ModuleHow to Add Chatter in the odoo 17 ERP Module
How to Add Chatter in the odoo 17 ERP Module
Celine George
 
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...
Levi Shapiro
 
Advantages and Disadvantages of CMS from an SEO Perspective
Advantages and Disadvantages of CMS from an SEO PerspectiveAdvantages and Disadvantages of CMS from an SEO Perspective
Advantages and Disadvantages of CMS from an SEO Perspective
Krisztián Száraz
 
Group Presentation 2 Economics.Ariana Buscigliopptx
Group Presentation 2 Economics.Ariana BuscigliopptxGroup Presentation 2 Economics.Ariana Buscigliopptx
Group Presentation 2 Economics.Ariana Buscigliopptx
ArianaBusciglio
 
Aficamten in HCM (SEQUOIA HCM TRIAL 2024)
Aficamten in HCM (SEQUOIA HCM TRIAL 2024)Aficamten in HCM (SEQUOIA HCM TRIAL 2024)
Aficamten in HCM (SEQUOIA HCM TRIAL 2024)
Ashish Kohli
 
CACJapan - GROUP Presentation 1- Wk 4.pdf
CACJapan - GROUP Presentation 1- Wk 4.pdfCACJapan - GROUP Presentation 1- Wk 4.pdf
CACJapan - GROUP Presentation 1- Wk 4.pdf
camakaiclarkmusic
 
A Survey of Techniques for Maximizing LLM Performance.pptx
A Survey of Techniques for Maximizing LLM Performance.pptxA Survey of Techniques for Maximizing LLM Performance.pptx
A Survey of Techniques for Maximizing LLM Performance.pptx
thanhdowork
 
MATATAG CURRICULUM: ASSESSING THE READINESS OF ELEM. PUBLIC SCHOOL TEACHERS I...
MATATAG CURRICULUM: ASSESSING THE READINESS OF ELEM. PUBLIC SCHOOL TEACHERS I...MATATAG CURRICULUM: ASSESSING THE READINESS OF ELEM. PUBLIC SCHOOL TEACHERS I...
MATATAG CURRICULUM: ASSESSING THE READINESS OF ELEM. PUBLIC SCHOOL TEACHERS I...
NelTorrente
 
S1-Introduction-Biopesticides in ICM.pptx
S1-Introduction-Biopesticides in ICM.pptxS1-Introduction-Biopesticides in ICM.pptx
S1-Introduction-Biopesticides in ICM.pptx
tarandeep35
 
"Protectable subject matters, Protection in biotechnology, Protection of othe...
"Protectable subject matters, Protection in biotechnology, Protection of othe..."Protectable subject matters, Protection in biotechnology, Protection of othe...
"Protectable subject matters, Protection in biotechnology, Protection of othe...
SACHIN R KONDAGURI
 
MASS MEDIA STUDIES-835-CLASS XI Resource Material.pdf
MASS MEDIA STUDIES-835-CLASS XI Resource Material.pdfMASS MEDIA STUDIES-835-CLASS XI Resource Material.pdf
MASS MEDIA STUDIES-835-CLASS XI Resource Material.pdf
goswamiyash170123
 
PIMS Job Advertisement 2024.pdf Islamabad
PIMS Job Advertisement 2024.pdf IslamabadPIMS Job Advertisement 2024.pdf Islamabad
PIMS Job Advertisement 2024.pdf Islamabad
AyyanKhan40
 
PCOS corelations and management through Ayurveda.
PCOS corelations and management through Ayurveda.PCOS corelations and management through Ayurveda.
PCOS corelations and management through Ayurveda.
Dr. Shivangi Singh Parihar
 
Pollock and Snow "DEIA in the Scholarly Landscape, Session One: Setting Expec...
Pollock and Snow "DEIA in the Scholarly Landscape, Session One: Setting Expec...Pollock and Snow "DEIA in the Scholarly Landscape, Session One: Setting Expec...
Pollock and Snow "DEIA in the Scholarly Landscape, Session One: Setting Expec...
National Information Standards Organization (NISO)
 

Recently uploaded (20)

Azure Interview Questions and Answers PDF By ScholarHat
Azure Interview Questions and Answers PDF By ScholarHatAzure Interview Questions and Answers PDF By ScholarHat
Azure Interview Questions and Answers PDF By ScholarHat
 
Reflective and Evaluative Practice...pdf
Reflective and Evaluative Practice...pdfReflective and Evaluative Practice...pdf
Reflective and Evaluative Practice...pdf
 
How to Build a Module in Odoo 17 Using the Scaffold Method
How to Build a Module in Odoo 17 Using the Scaffold MethodHow to Build a Module in Odoo 17 Using the Scaffold Method
How to Build a Module in Odoo 17 Using the Scaffold Method
 
The basics of sentences session 5pptx.pptx
The basics of sentences session 5pptx.pptxThe basics of sentences session 5pptx.pptx
The basics of sentences session 5pptx.pptx
 
Introduction to AI for Nonprofits with Tapp Network
Introduction to AI for Nonprofits with Tapp NetworkIntroduction to AI for Nonprofits with Tapp Network
Introduction to AI for Nonprofits with Tapp Network
 
Fresher’s Quiz 2023 at GMC Nizamabad.pptx
Fresher’s Quiz 2023 at GMC Nizamabad.pptxFresher’s Quiz 2023 at GMC Nizamabad.pptx
Fresher’s Quiz 2023 at GMC Nizamabad.pptx
 
How to Add Chatter in the odoo 17 ERP Module
How to Add Chatter in the odoo 17 ERP ModuleHow to Add Chatter in the odoo 17 ERP Module
How to Add Chatter in the odoo 17 ERP Module
 
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...
 
Advantages and Disadvantages of CMS from an SEO Perspective
Advantages and Disadvantages of CMS from an SEO PerspectiveAdvantages and Disadvantages of CMS from an SEO Perspective
Advantages and Disadvantages of CMS from an SEO Perspective
 
Group Presentation 2 Economics.Ariana Buscigliopptx
Group Presentation 2 Economics.Ariana BuscigliopptxGroup Presentation 2 Economics.Ariana Buscigliopptx
Group Presentation 2 Economics.Ariana Buscigliopptx
 
Aficamten in HCM (SEQUOIA HCM TRIAL 2024)
Aficamten in HCM (SEQUOIA HCM TRIAL 2024)Aficamten in HCM (SEQUOIA HCM TRIAL 2024)
Aficamten in HCM (SEQUOIA HCM TRIAL 2024)
 
CACJapan - GROUP Presentation 1- Wk 4.pdf
CACJapan - GROUP Presentation 1- Wk 4.pdfCACJapan - GROUP Presentation 1- Wk 4.pdf
CACJapan - GROUP Presentation 1- Wk 4.pdf
 
A Survey of Techniques for Maximizing LLM Performance.pptx
A Survey of Techniques for Maximizing LLM Performance.pptxA Survey of Techniques for Maximizing LLM Performance.pptx
A Survey of Techniques for Maximizing LLM Performance.pptx
 
MATATAG CURRICULUM: ASSESSING THE READINESS OF ELEM. PUBLIC SCHOOL TEACHERS I...
MATATAG CURRICULUM: ASSESSING THE READINESS OF ELEM. PUBLIC SCHOOL TEACHERS I...MATATAG CURRICULUM: ASSESSING THE READINESS OF ELEM. PUBLIC SCHOOL TEACHERS I...
MATATAG CURRICULUM: ASSESSING THE READINESS OF ELEM. PUBLIC SCHOOL TEACHERS I...
 
S1-Introduction-Biopesticides in ICM.pptx
S1-Introduction-Biopesticides in ICM.pptxS1-Introduction-Biopesticides in ICM.pptx
S1-Introduction-Biopesticides in ICM.pptx
 
"Protectable subject matters, Protection in biotechnology, Protection of othe...
"Protectable subject matters, Protection in biotechnology, Protection of othe..."Protectable subject matters, Protection in biotechnology, Protection of othe...
"Protectable subject matters, Protection in biotechnology, Protection of othe...
 
MASS MEDIA STUDIES-835-CLASS XI Resource Material.pdf
MASS MEDIA STUDIES-835-CLASS XI Resource Material.pdfMASS MEDIA STUDIES-835-CLASS XI Resource Material.pdf
MASS MEDIA STUDIES-835-CLASS XI Resource Material.pdf
 
PIMS Job Advertisement 2024.pdf Islamabad
PIMS Job Advertisement 2024.pdf IslamabadPIMS Job Advertisement 2024.pdf Islamabad
PIMS Job Advertisement 2024.pdf Islamabad
 
PCOS corelations and management through Ayurveda.
PCOS corelations and management through Ayurveda.PCOS corelations and management through Ayurveda.
PCOS corelations and management through Ayurveda.
 
Pollock and Snow "DEIA in the Scholarly Landscape, Session One: Setting Expec...
Pollock and Snow "DEIA in the Scholarly Landscape, Session One: Setting Expec...Pollock and Snow "DEIA in the Scholarly Landscape, Session One: Setting Expec...
Pollock and Snow "DEIA in the Scholarly Landscape, Session One: Setting Expec...
 

Transportation Method Operation Research

  • 1. Operations Research Chapter : Transportation Find Initial Basic Feasible Solution-IBFS Using North West Corner Method-- NWCM , Least Cost Method-- LCM and Vogel’s Approximation Method-- VAM Optimality Test using Modified Distribution Method- MODI method. Variation in transportation Unbalance Supply and Demand Degeneracy and its resolution Maximization Problem
  • 2. Introduction • Transportation Models are used to find out optimum cost of transportation of goods. • Company ABC has three plants at Ahmedabad, Surat and Rajkot and four demand stations at Visnagar, Baroda and Vapi and Bhuj. We can formulate transportation matrix as below Visnagar Baroda Vapi Bhuj Capacity Ahmedabad 10 20 30 40 7 Surat 20 30 10 60 8 Rajkot 20 15 40 20 5 Demand 2 7 6 5 20
  • 3. Here, In table cell value 10,20,30,40 Rs. shows cost of transportation. Last column value shows daily maximum supply. Last row value shows daily maximum demand of each city.
  • 4. Terms: 1) Balanced Model If, Total Supply=Total Demand 2) Non Degenerate Solution If, m+n-1=number of allocated cell Where, m=total number of rows n=total number of columns 3) Feasible solution All supply and demand constraints are satisfied.
  • 5. Methods to find out Initial Basic Feasible Solution (IBFS): 1. NWCM-- North West Corner Method 2. LCM-- Least Cost Method 3. VAM-- Vogel’s Approximation Method
  • 6. Example 1 : (Problem Type: Balanced Problem) A Company has 3 production facilities S1, S2 and S3 with production capacity of 7, 9 and 18 units per week of a product, respectively. These units are to be shipped to 4 warehouses D1, D2, D3 and D4 with requirement of 5,6,7 and 14 units per week, respectively. The transportation costs (in rupees) per unit between factories to warehouses are given in the table below.
  • 7. D1 D2 D3 D4 Capacity S1 19 30 50 10 7 S2 70 30 40 60 9 S3 40 8 70 20 18 Demand 5 8 7 14 34 Find initial basic feasible solution for given problem by using North-West corner method if the object is to minimize the total transportation cost.
  • 8. Demand Destination D1 D2 D3 D4 Supply Supply Station S1 19 (5) 30 50 10 7 S2 70 30 40 60 9 S3 40 8 70 20 18 Demand 5 8 7 14 34/34 Solution: North-West corner method---NWCM Step 1 : Identify North west corner from all cost cell. Here S1D1 is North west corner. Do allocation in this cell. Demand of D1 = 5 which is less than possible supply from S1= 7. Here 5<7...So allocate (5) in S1D1 Cell.
  • 9. Demand Destination D1 D2 D3 D4 Supply Supply Station S1 19 (5) 30 (2) 50 10 7 S2 70 30 40 60 9 S3 40 8 70 20 18 Demand 5 8 7 14 34/34 •Step 2 : Now no need to consider D1 column as its demand 5 is completed. • Identify North west corner from all remaining cost cell. •Here S1D2 is North west corner. • Do allocation in this cell. •Demand of D1 = 8. Available supply from S1=7-5=2 Here, 2<8...So allocate (2) in S1D2 Cell.
  • 10. Demand Destination D1 D2 D3 D4 Supply Supply Station S1 19 (5) 30 (2) 50 10 7 S2 70 30 (6) 40 60 9 S3 40 8 70 20 18 Demand 5 8 7 14 34/34 •Step 3 : Now no need to consider D1 column and S1 row.As its constraints 5 and 7 are satisfied. • Identify North west corner from all remaining cost cell...Here S2D2 is North west corner. • Do allocation in this cell. •Remaining Demand of D2 = 8-2 =6. Possible supply from S2=9. Here, 6<9..So allocate (6) in S2D2 Cell.
  • 11. Demand Destination D1 D2 D3 D4 Supply Supply Station S1 19 (5) 30 (2) 50 10 7 S2 70 30 (6) 40 (3) 60 9 S3 40 8 70 20 18 Demand 5 8 7 14 34/34 •Step 4 : Now no need to consider D1-D2 column and S1 row. • Identify North west corner from all remaining cost cell. •Here S2D3 is North west corner. • Do allocation in this cell. •Demand of D3 = 7. Available supply from S2=9-6=3. Here, 3<7..So allocate (3) in S2D3 Cell.
  • 12. Demand Destination D1 D2 D3 D4 Supply Supply Station S1 19 (5) 30 (2) 50 10 7 S2 70 30 (6) 40 (3) 60 9 S3 40 8 70 (4) 20 18 Demand 5 8 7 14 34/34 •Step 5 : Now no need to consider D1-D2 column and S1-S2 row. • Identify North west corner from all remaining cost cell. •Here S3D3 is North west corner. • Do allocation in this cell. •Remaining Demand of D3 = 7-3=4 . Possible supply from S2=18. So allocate (4) in S3D3 Cell.
  • 13. Demand Destination D1 D2 D3 D4 Supply Supply Station S1 19 (5) 30 (2) 50 10 7 S2 70 30 (6) 40 (3) 60 9 S3 40 8 70 (4) 20 (14) 18 Demand 5 8 7 14 34/34 •Step 6 : Here remaining cell is S3D4. • Do allocation in this cell. •Demand of D3 = 14 . • Possible supply from S3=18-4=14. •So allocate (14) in S3D4 Cell.
  • 14. From previous table, The minimum total transportation cost = (19×5)+(30×2)+(30×6)+(40×3)+(70×4)+(20×14) =1015 Rs.--------Answer. Here, the number of allocated cells = 6 is equal to m + n - 1 = 3 + 4 - 1 = 6 So, ∴ This solution is non-degenerate----Answer. Where, m= total rows = 3. n= total columns = 4.
  • 15. Example 2: (Similar as example 1 NWCM METHOD) Find Solution using North-West Corner method D1 D2 D3 D4 Supply S1 11 13 17 14 250 S2 16 18 14 10 300 S3 21 24 13 10 400 Demand 200 225 275 250 950/950 Type-Balanced supply and demand
  • 16. D1 D2 D3 D4 Supply S1 11 (200) 13 17 14 250 S2 16 18 14 10 300 S3 21 24 13 10 400 Demand 200 225 275 250
  • 17. D1 D2 D3 D4 Supply S1 11 (200) 13 (50) 17 14 250 S2 16 18 14 10 300 S3 21 24 13 10 400 Demand 200 225 275 250
  • 18. D1 D2 D3 D4 Supply S1 11 (200) 13 (50) 17 14 250 S2 16 18 (175) 14 10 300 S3 21 24 13 10 400 Demand 200 225 275 250
  • 19. D1 D2 D3 D4 Supply S1 11 (200) 13 (50) 17 14 250 S2 16 18 (175) 14 (125) 10 300 S3 21 24 13 10 400 Demand 200 225 275 250
  • 20. D1 D2 D3 D4 Supply S1 11 (200) 13 (50) 17 14 250 S2 16 18 (175) 14 (125) 10 300 S3 21 24 13 (150) 10 400 Demand 200 225 275 250
  • 21. D1 D2 D3 D4 Supply S1 11 (200) 13 (50) 17 14 250 S2 16 18 (175) 14 (125) 10 300 S3 21 24 13 (150) 10 (250) 400 Demand 200 225 275 250
  • 22. The minimum total transportation cost = (11×200) +(13×50)+(18×175)+(14×125)+(13×150)+(10×250) =12200 Here, the number of allocated cells = 6 is equal to m + n - 1 = 3 + 4 - 1 = 6 ∴ This solution is non-degenerate
  • 23. Example 3 (Problem Type-Unbalanced supply and demand example) Find Solution using North-West Corner method
  • 24. D1 D2 D3 Supply S1 4 8 8 76 S2 16 24 16 82 S3 8 16 24 77 Demand 72 102 41 Here Total Demand = 215 is less than Total Supply = 235
  • 25. D1 D2 D3 Ddummy Supply S1 4 8 8 0 76 S2 16 24 16 0 82 S3 8 16 24 0 77 Demand 72 102 41 20 So add a dummy demand column with 0 unit cost with allocation 20. Now, the modified table is
  • 26. D1 D2 D3 Ddummy Supply S1 4 (72) 8 8 0 76 S2 16 24 16 0 82 S3 8 16 24 0 77 Demand 72 102 41 20
  • 27. D1 D2 D3 Ddummy Supply S1 4 (72) 8 (4) 8 0 76 S2 16 24 16 0 82 S3 8 16 24 0 77 Demand 72 102 41 20
  • 28. D1 D2 D3 Ddummy Supply S1 4 (72) 8 (4) 8 0 76 S2 16 24 (82) 16 0 82 S3 8 16 24 0 77 Demand 72 102 41 20
  • 29. D1 D2 D3 Ddummy Supply S1 4 (72) 8 (4) 8 0 76 S2 16 24 (82) 16 0 82 S3 8 16 (16) 24 0 77 Demand 72 102 41 20
  • 30. D1 D2 D3 Ddummy Supply S1 4 (72) 8 (4) 8 0 76 S2 16 24 (82) 16 0 82 S3 8 16 (16) 24 (41) 0 77 Demand 72 102 41 20
  • 31. D1 D2 D3 Ddummy Supply S1 4 (72) 8 (4) 8 0 76 S2 16 24 (82) 16 0 82 S3 8 16 (16) 24 (41) 0 (20) 77 Demand 72 102 41 20 Initial feasible solution ----IBFS is
  • 32. The minimum total transportation cost =(4×72)+(8×4)+(24×82)+(16×16)+(24×41)+(0×20)=3528 Here, the number of allocated cells = 6 is equal to m + n - 1 = 3 + 4 - 1 = 6 ∴ This solution is non-degenerate
  • 33. Example 4: Find Solution using Least Cost method D1 D2 D3 D4 Supply S1 19 30 50 10 7 S2 70 30 40 60 9 S3 40 8 70 20 18 Demand 5 8 7 14 34/34
  • 34. Step-1. Identify Least Cost value Out of all Cost values… Here 8 Rs. is least Cost Step2. Do First allocation in this S3-D2 cell D2 demand 8 is less than S3 supply 18, so allocate 8 Now no need to consider D2 column value further. D1 D2 D3 D4 Supply S1 19 30 50 10 7 S2 70 30 40 60 9 S3 40 8 (8) 70 20 18 Demand 5 8 7 14
  • 35. Step 3: Identify next to smallest cost value that is 10 Rs. Step 4: Do allocate in S1-D4 Cell. S1 Supply 7 is less than D4 Demand 14 so allocate 7 Now no need to consider S1 row value further. D1 D2 D3 D4 Supply S1 19 30 50 10 (7) 7 S2 70 30 40 60 9 S3 40 8 (8) 70 20 18 Demand 5 8 7 14
  • 36. Follow similar steps. Next smallest cost value is 20 (As we have no need to consider S1 row values). Possible Allocation in S3-D4 cell is 7 D1 D2 D3 D4 Supply S1 19 30 50 10 (7) 7 S2 70 30 40 60 9 S3 40 8 (8) 70 20 (7) 18 Demand 5 8 7 14
  • 37. Here, next two cost 40 Rs. are same in two cell . It is Situation of tie. Do allocate where maximum allocation possible that is in cell S2-D3. Allocate 7 , as demand in D3 is 7 which is less than supply in S2, 9. D1 D2 D3 D4 Supply S1 19 30 50 10 (7) 7 S2 70 30 40 (7) 60 9 S3 40 8 (8) 70 20 (7) 18 Demand 5 8 7 14
  • 38. Next allocation is in S3-D1 that is 18-8-7=3 D1 D2 D3 D4 Supply S1 19 30 50 10 (7) 7 S2 70 30 40 (7) 60 9 S3 40 (3) 8 (8) 70 20 (7) 18 Demand 5 8 7 14
  • 39. Next allocation is in S2-D1 that is 9-7= 5-3 =2 D1 D2 D3 D4 Supply S1 19 30 50 10 (7) 7 S2 70 (2) 30 40 (7) 60 9 S3 40 (3) 8 (8) 70 20 (7) 18 Demand 5 8 7 14
  • 40. The minimum total transportation cost = (10×7)+(70×2)+(40×7)+(40×3)+(8×8)+(20×7) = 814 Rs. Here, m=total rows=3 n=total columns=4 the number of allocated cells = 6 is equal to m + n - 1 = 3 + 4 - 1 = 6 ∴ This solution is non-degenerate
  • 41. Example 5: LCM Method- Practice Problem D1 D2 D3 D4 Supply S1 11 13 17 14 250 S2 16 18 14 10 300 S3 21 24 13 10 (250) 400 Demand 200 225 275 250
  • 42. D1 D2 D3 D4 Supply S1 11 (200) 13 17 14 250 S2 16 18 14 10 300 S3 21 24 13 10 (250) 400 Demand 200 225 275 250
  • 43. D1 D2 D3 D4 Supply S1 11 (200) 13 (50) 17 14 250 S2 16 18 14 10 300 S3 21 24 13 10 (250) 400 Demand 200 225 275 250
  • 44. D1 D2 D3 D4 Supply S1 11 (200) 13 (50) 17 14 250 S2 16 18 14 10 300 S3 21 24 13 (150) 10 (250) 400 Demand 200 225 275 250
  • 45. D1 D2 D3 D4 Supply S1 11 (200) 13 (50) 17 14 250 S2 16 18 14 (125) 10 300 S3 21 24 13 (150) 10 (250) 400 Demand 200 225 275 250
  • 46. D1 D2 D3 D4 Supply S1 11 (200) 13 (50) 17 14 250 S2 16 18 (175) 14 (125) 10 300 S3 21 24 13 (150) 10 (250) 400 Demand 200 225 275 250
  • 47. The minimum total transportation cost = 11*200 + 13*50 + 18*175 + 14*125 + 13*150 + 10*250 = 12200 Rs. Here, the number of allocated cells = 6 is equal to m + n - 1 = 3 + 4 - 1 = 6 ∴ This solution is non-degenerate
  • 48. Example 6: Solve example using Vogel’s Approximation Method (VAM Method) D1 D2 D3 D4 Supply S1 19 30 50 10 7 S2 70 30 40 60 9 S3 40 8 70 20 18 Demand 5 8 7 14
  • 49. D1 D2 D3 D4 Supply Row Difference S1 19 30 50 10 7 9=19-10 S2 70 30 40 60 9 10=40-30 S3 40 8 70 20 18 12=20-8 Demand 5 8 7 14 Column difference 21=40-19 22=30-8 10=50-40 10=20-10
  • 50. D1 D2 D3 D4 Supply Row Differences S1 19 30 50 10 7 9 S2 70 30 40 60 9 10 S3 40 8(8) 70 20 18 12 Demand 5 8 7 14 34/34 Column Differences 21 22 10 10
  • 51. D1 D2 D3 D4 Supply Row Differences S1 19(5) 30 50 10 7 9 9 S2 70 30 40 60 9 10 20 S3 40 8(8) 70 20 18 12 20 Demand 5 8 7 14 34/34 Column Differences 21 21 22 -- 10 10 10 10
  • 52. D1 D2 D3 D4 Supply Row Differences S1 19(5) 30 50 10 7 9 9 40 S2 70 30 40 60 9 10 20 20 S3 40 8(8) 70 20(10) 18 12 20 50 Demand 5 8 7 14 34/34 Column Differences 21 21 -- 22 -- -- 10 10 10 10 10 10
  • 53. D1 D2 D3 D4 Supply Row Differences S1 19(5) 30 50 10(2) 7 9 9 40 40 S2 70 30 40 60 9 10 20 20 20 S3 40 8(8) 70 20(10) 18 12 20 50 - Demand 5 8 7 14 34/34 Column Differences 21 21 -- -- 22 -- -- -- 10 10 10 10 10 10 10 50
  • 54. D1 D2 D3 D4 Supply Row Differences S1 19(5) 30 50 10(2) 7 9 9 40 40 - S2 70 30 40 60(2) 9 10 20 20 20 20 S3 40 8(8) 70 20(10) 18 12 20 50 - - Demand 5 8 7 14 34/34 Column Differences 21 21 -- -- -- 22 -- -- -- -- 10 10 10 10 40 10 10 10 50 60
  • 55. D1 D2 D3 D4 Supply Row Differences S1 19(5) 30 50 10(2) 7 9 9 40 40 - - S2 70 30 40(7) 60(2) 9 10 20 20 20 20 40 S3 40 8(8) 70 20(10) 18 12 20 50 - - - Demand 5 8 7 14 34/34 Column Differences 21 21 -- -- -- -- 22 -- -- -- -- -- 10 10 10 10 40 40 10 10 10 50 60 --
  • 56. The minimum total transportation cost = 19×5 + 10×2 + 40×7 + 60×2 + 8×8 + 20×10 = 779 Rs. Here, the number of allocated cells = 6 is equal to m + n - 1 = 3 + 4 - 1 = 6 ∴ This solution is non-degenerate
  • 57. Example 7 Find Solution using Vogel's Approximation method D1 D2 D3 D4 Supply S1 11 13 17 14 250 S2 16 18 14 10 300 S3 21 24 13 10 400 Demand 200 225 275 250
  • 58. D1 D2 D3 D4 Supply Row Differences S1 11(200) 13 17 14 250 2 - ------ S2 16 18 14 10 300 4 ----- S3 21 24 13 10 400 3 - Demand 200 225 275 250 Column Differenc es 5 -- -- 5 -- 1 0
  • 59. D1 D2 D3 D4 Supply Row Differences S1 11(200) 13(50) 17 14 250 2 1--- ------ S2 16 18 14 10 300 4 4-- ------- S3 21 24 13 10 400 3 3-- Deman d 200 225 275 250 Column Differen ces 5 -- -- -- 5 5 -- 1 1 0 0 0 0
  • 60. D1 D2 D3 D4 Supply Row Differences S1 11(200) 13(50) 17 14 250 2 1--- ------ S2 16 18(175) 14 10 300 4 4--4 S3 21 24 13 10 400 3 3--3 Demand 200 225 275 250 Column Differenc es 5 -- -- -- -- -- 5 5 6 -- -- -- 1 1 1 -- 0 0 0 0
  • 61. D1 D2 D3 D4 Supply Row Differences S1 11(200) 13(50) 17 14 250 2 1--- ------ S2 16 18(175) 14 10(125) 300 4 4--4 4------- S3 21 24 13 10 400 3 3--3 3- Demand 200 225 275 250 Column Differenc es 5 -- -- -- -- -- 5 5 6 -- -- -- 1 1 1 1 -- 0 0 0 0
  • 62. D1 D2 D3 D4 Supply Row Differences S1 11(200) 13(50) 17 14 250 2 1--- ------ S2 16 18(175) 14 10(125) 300 4 4--4 4------- S3 21 24 13(275) 10 400 3 3--3 3-3- Demand 200 225 275 250 Column Differenc es 5 -- -- -- -- -- 5 5 6 -- -- -- 1 1 1 1 13 -- 0 0 0 0 10
  • 63. D1 D2 D3 D4 Supply Row Differences S1 11(200) 13(50) 17 14 250 2 1--- ------ S2 16 18(175) 14 10(125) 300 4 4--4 4------- S3 21 24 13(275) 10(125) 400 3 3--3 3-3-10 Demand 200 225 275 250 Column Differenc es 5 -- -- -- -- -- 5 5 6 -- -- -- 1 1 1 1 13 -- 0 0 0 0 10 10
  • 64. D1 D2 D3 D4 Supply Row Differences S1 11(200) 13(50) 17 14 250 2 | 1 | -- | -- | -- | -- | S2 16 18(175) 14 10(125) 300 4 | 4 | 4 | 4 | -- | -- | S3 21 24 13(275) 10(125) 400 3 | 3 | 3 | 3 | 3 | 10 | Demand 200 225 275 250 Column Differences 5 -- -- -- -- -- 5 5 6 -- -- -- 1 1 1 1 13 -- 0 0 0 0 10 10
  • 65. The minimum total transportation cost =11×200+13×50+18×175+10×125+13×275+10×125 =12075 Here, the number of allocated cells = 6 is equal to m + n - 1 = 3 + 4 - 1 = 6 ∴ This solution is non-degenerate
  • 66. Optimality Test Question–Modified Distribution Method --MODI Method Steps (Rule) ---7 Marks
  • 67. Step-1:Find an initial basic feasible solution--IBFS--using any one of the three methods NWCM, LCM or VAM. Step-2:Find ui and vj for rows and columns. To start a. assign 0 to ui or vj where maximum number of allocation in a row or column respectively. b. Calculate other ui's and vj's using cij=ui+vj, for all occupied cells. Step-3: For all unoccupied cells (i , j), calculate dij=cij-(ui+vj)
  • 68. Step-4:Check the sign of dij a. If dij>0, then current basic feasible solution is optimal and stop this procedure. b. If dij=0 then alternative solution exists, with different set allocation and same transportation cost. C. If dij<0, then the given solution is not an optimal solution and further improvement in the solution is possible. Step-5:Select the unoccupied cell with the largest negative value of dij
  • 69. Step-6:Draw a closed path (or loop) from the unoccupied cell (selected in the previous step). Mark (+) and (-) sign alternatively at each corner, starting from the original unoccupied cell. Step-7: Repeat Step-2 to step-7 until optimal solution is obtained. This procedure stops when all dij≥0 for unoccupied cells
  • 70. Example 7: Find optimal solution using MODI Method D1 D2 D3 D4 Supply S1 19 30 50 10 7 S2 70 30 40 60 9 S3 40 8 70 20 18 Demand 5 8 7 14
  • 71. D1 D2 D3 D4 Supply S1 19(5) 30 50 10(2) 7 S2 70 30 40(7) 60(2) 9 S3 40 8(8) 70 20(10) 18 Demand 5 8 7 14 34/34 Step 1: Find solution using VAM method
  • 72. Step-2:Find ui and vj for rows and columns. To start a. assign 0 to ui or vj where maximum number of allocation in a row or column respectively. b. Calculate other ui's and vj's using cij=ui+vj, for all occupied cells.
  • 73. D1 D2 D3 D4 Supply S1 19(5) 30 50 10(2) 7 u1= S2 70 30 40(7) 60(2) 9 u2= S3 40 8(8) 70 20(10) 18 u3= Demand 5 8 7 14 34/34 V1= V2= V3= v4= 0
  • 74. Iteration-1 of optimality test Find ui and vj for all occupied cells(i , j), where cij=ui+vj= cost from i row to j column 1. Substituting, v4=0, we get 2.c14=u1+v4⇒u1=c14-v4⇒u1=10-0⇒u1=10 3.c11=u1+v1⇒v1=c11-u1⇒v1=19-10⇒v1=9
  • 75. D1 D2 D3 D4 Supply S1 19(5) 30 50 10(2) 7 u1= 10 S2 70 30 40(7) 60(2) 9 u2= S3 40 8(8) 70 20(10) 18 u3= Demand 5 8 7 14 34/34 v1= 9 v2= v3= v4= 0
  • 77. D1 D2 D3 D4 Supply S1 19(5) 30 50 10(2) 7 u1= 10 S2 70 30 40(7) 60(2) 9 u2= 60 S3 40 8(8) 70 20(10) 18 u3= 20 Demand 5 8 7 14 34/34 v1= 9 v2= -12 v3= -20 v4= 0
  • 78. Step-3: For all unoccupied cells (i,j), calculate dij=cij-(ui+vj) 1.d12=c12-(u1+v2)=30-(10-12)=32 2.d13=c13-(u1+v3)=50-(10-20)=60 3.d21=c21-(u2+v1)=70-(60+9)=1 4.d22=c22-(u2+v2)=30-(60-12)=-18 5.d31=c31-(u3+v1)=40-(20+9)=11 6.d33=c33-(u3+v3)=70-(20-20)=70
  • 79. D1 D2 D3 D4 Supply S1 19(5) 30 [32] 50 [60] 10(2) 7 u1= 10 S2 70 [1] 30 [-18] 40(7) 60(2) 9 u2= 60 S3 40 [11] 8(8) 70 [70] 20(10) 18 u3= 20 Demand 5 8 7 14 34/34 v1= 9 v2= -12 v3= -20 v4= 0
  • 80. Step-4:Check the sign of dij a. If dij>0, then current basic feasible solution is optimal and stop this procedure. b. If dij=0 then alternative solution exists, with different set allocation and same transportation cost. C. If dij<0, then the given solution is not an optimal solution and further improvement in the solution is possible. Here d22= -18 which is less than zero, so it is non optimal solution
  • 81. Step-5:Select the unoccupied cell with the largest negative value of dij Step-6:Draw a closed path (or loop) from the unoccupied cell (selected in the previous step). Mark (+) and (-) sign alternatively at each corner, starting from the original unoccupied cell. Now choose the minimum negative value from all dij (opportunity cost) = d22 = [-18] and draw a closed path from S2D2. Closed path is S2D2→S2D4→S3D4→S3D2
  • 82. Closed path loop and plus/minus sign allocation… 1. Select the minimum value from cells marked with (-) sign of the closed path. 2. Assign this value to selected unoccupied cell (So unoccupied cell becomes occupied 3. Add this value to the other occupied cells marked with (+) sign. 4. Subtract this value to the other occupied cells marked with (-) sign.
  • 83. D1 D2 D3 D4 Supply S1 19(5) 30 [32] 50 [60] 10(2) 7 u1= 10 S2 70 [1] 30 [-18] + 40(7) 60(2) - 9 u2= 60 S3 40 [11] 8(8) - 70 [70] 20(10) + 18 u3= 20 Demand 5 8 7 14 34/34 v1= 9 v2= -12 v3= -20 v4= 0
  • 84. D1 D2 D3 D4 Supply S1 19(5) 30 50 10(2) 7 S2 70 30(2) 40(7) 60 9 S3 40 8(6) 70 20(12) 18
  • 85. Step-7: Repeat Step-2 to step-7 until optimal solution is obtained. This procedure stops when all dij≥0 for unoccupied cells
  • 86. D1 D2 D3 D4 Supply ui S1 19 (5) 30 [32] 50 [42] 10 (2) 7 u1=0 S2 70 [19] 30 (2) 40 (7) 60 [18] 9 u2=32 S3 40 [11] 8 (6) 70 [52] 20 (12) 18 u3=10 Demand 5 8 7 14 vj v1=19 v2=-2 v3=8 v4=10
  • 87. Since all dij≥0. So final optimal solution is arrived.
  • 88. D1 D2 D3 D4 Supply S1 19(5) 30 50 10(2) 7 S2 70 30(2) 40(7) 60 9 S3 40 8(6) 70 20(12) 18 The minimum total transportation cost = 19×5 + 10×2 + 30×2 + 40×7 + 8×6 + 20×12 = 743
  • 89. Variations in Transportation 1. Unbalance Supply and Demand 2. Degeneracy and its resolution 3. Maximization Problem
  • 90. 1. Unbalance Supply and Demand Solution : Add dummy row or column Supply less  Add Dummy Row Demand less  Add Dummy Column
  • 91. D1 D2 D3 Supply S1 5 4 7 120 S2 10 15 12 80 S3 3 5 12 60 Demand 150 80 50 280/260 Unbalance Supply and Demand Here, Total supply = 260 Total Demand = 280 Add dummy row Solution : Supply 260 is less than demand 280,
  • 92. D1 D2 D3 Supply S1 5 4 7 120 S2 10 15 12 80 S3 3 5 12 60 Sdummy 0 0 0 20 Demand 150 80 50 280/280 Now, Total supply = Total Demand = 280, So it is balanced Problem, Now we can find IBFS using NWCM, LCM Or VAM Method. Supply less  Add Dummy Row
  • 93. D1 D2 D3 Supply S1 5 4 7 100 S2 10 15 12 100 S3 3 5 12 50 Demand 80 80 50 210/250 Unbalance Supply and Demand Here, Total supply = 250 Total Demand = 210 Solution : Demand 210 is less than supply 250, Add dummy column
  • 94. D1 D2 D3 Ddummy Supply S1 5 4 7 0 100 S2 10 15 12 0 100 S3 3 5 12 0 50 Demand 80 80 50 40 250/250 Now, Total supply = Total Demand = 250, So it is balanced Problem, Now we can find IBFS using NWCM, LCM Or VAM Method. Demand less  Add Dummy Column
  • 95. 2. Degeneracy and its resolution (Convert Degenerate solution into non degenerate solution) Solution : • To resolve degeneracy, we make use of an artificial quantity delta (Δ ) • The quantity Δ is assigned to that unoccupied cell, which has the minimum transportation cost.
  • 96. D1 D2 D3 Supply S1 8(70) 5 6(50) 120 S2 15 10(80) 12 80 S3 3(80) 9 10 80 Demand 150 80 50 280/280 Initial feasible solution by VAM method is Here, the number of allocated cells = 4, which is one less than m + n - 1 = 3 + 3 - 1 = 5 ∴ This solution is degenerate
  • 97. Here, the number of allocated cells = 4, which is one less than m + n - 1 = 3 + 3 - 1 = 5 ∴ This solution is degenerate To Make it Non degenerate, The quantity Δ is assigned to S1D2, which has the minimum transportation cost = 5.
  • 98. D1 D2 D3 Supply S1 8(70) 5 (Δ) 6(50) 120 S2 15 10(80) 12 80 S3 3(80) 9 10 80 Demand 150 80 50 280/280 Here, Now Number of allocated cell = 5 And m+n-1=5, Now, Solution is non degenerate. Now we can do optimality Test Minimum transportation cost = 5 Rs. Here Assign (Δ) in this (S1, D2) cell
  • 99. 3. Maximization Problem Solution: Convert into Minimization Problem How ?? :: By subtracting all cost values from maximum cost value. ----Than apply LCM, NWCM Or VAM Method
  • 100. In data it is mentioned-Find maximum profit . D1 D2 D3 D4 Supply S1 10 20 30 20 7 S2 30 10 40 60 9 S3 40 50 70 20 18 Demand 5 8 7 14 10, 20, 30, 20…etc are profit values. Convert into Minimization problem subtracting all values from maximum value (70 Rs).
  • 101. Convert into Minimization problem subtracting all values from maximum value (70 Rs). Updated New Table is below, D1 D2 D3 D4 Supply S1 60 50 40 50 7 S2 40 60 30 10 9 S3 30 20 0 50 18 Demand 5 8 7 14 Now find IBFS using NWCM, LCM or VAM Method.
  • 102. Summery Of Transportation Chapter  1. Find Initial Basic Feasible Solution-IBFS Using a) North West Corner Method--NWCM , b) Least Cost Method--LCM and c) Vogel’s Approximation Method--VAM  2. Optimality Test using Modified Distribution Method- MODI method.  3. Variation in transportation a) Unbalance Supply and Demand b) Degeneracy and its resolution c) Maximization Problem