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7. Heuristic method-1 example ( Enter your problem )
Algorithm and examples
  1. Algorithm & Example-1
  2. Example-2
  3. Unbalanced supply and demand example
Other related methods
  1. north-west corner method
  2. least cost method
  3. vogel's approximation method
  4. Row minima method
  5. Column minima method
  6. Russell's approximation method
  7. Heuristic method-1
  8. Heuristic method-2
  9. modi method (optimal solution)
  10. stepping stone method (optimal solution)

6. Russell's approximation method
(Previous method)
2. Example-2
(Next example)

1. Algorithm & Example-1





Algorithm
Heuristic Method-1:
Step-1: Calculate the difference between the two lowest cost cells (called Penalty) for each row and column. These are called as row and column penalties, P, respectively.
Step-2: Add the cost of cells for each row and column. These summations are called row and column cost, T, respectively.
Step-3: Compute the product of penalty 'P' and the total cost 'T', that is PT for each row and column.
Step-4: Identify the row/column having lowest 'PT'.
Step-5: Choose the cell having minimum cost in row/column identified in Step-4.
Step-6: Make maximum feasible allocation to the cell chosen in Step-5, if the cost of this cell is also minimum in its column/row. Otherwise allocation is avoided and goto Step-7.
Step-7: Identify the row/column having next to lowest 'PT'.
Step-8: Choose the cell having minimum cost in row/column identified in step 7.
Step-9: Make maximum feasible allocation to the cell chosen in Step-8.
Step-10: Cross out the satisfied row/column.
Step-11: Repeat the procedure until all the requirements are satisfied.

Example-1
Find Solution using Heuristic method-1
D1D2D3D4Supply
S1193050107
S2703040609
S3408702018
Demand58714


Solution:
TOTAL number of supply constraints : 3
TOTAL number of demand constraints : 4
Problem Table is
`D_1``D_2``D_3``D_4`Supply
`S_1`193050107
`S_2`703040609
`S_3`408702018
Demand58714


Table-1
`D_1``D_2``D_3``D_4`SupplyRow Penalty (P)Total (T)P`xx`T
`S_1`193050107`9=19-10`109`981=9xx109`
`S_2`703040609`10=40-30`200`2000=10xx200`
`S_3`408702018`12=20-8`138`1656=12xx138`
Demand58714
Column
Penalty (P)
`21=40-19``22=30-8``10=50-40``10=20-10`
Total (T)1296816090
P`xx`T`2709=21xx129``1496=22xx68``1600=10xx160``900=10xx90`


The lowest PT = 900, occurs in column `D_4`.

The minimum `c_(ij)` in this column is `c_14` = 10.

The maximum allocation in this cell is min(7,14) = 7.
It satisfy supply of `S_1` and adjust the demand of `D_4` from 14 to 7 (14 - 7 = 7).

Table-2
`D_1``D_2``D_3``D_4`SupplyRow Penalty (P)Total (T)P`xx`T
`S_1`19305010(7)0--109--
`S_2`703040609`10=40-30`200`2000=10xx200`
`S_3`408702018`12=20-8`138`1656=12xx138`
Demand5877
Column
Penalty (P)
`30=70-40``22=30-8``30=70-40``40=60-20`
Total (T)1296816090
P`xx`T`3870=30xx129``1496=22xx68``4800=30xx160``3600=40xx90`


The lowest PT = 1496, occurs in column `D_2`.

The minimum `c_(ij)` in this column is `c_32` = 8.

The maximum allocation in this cell is min(18,8) = 8.
It satisfy demand of `D_2` and adjust the supply of `S_3` from 18 to 10 (18 - 8 = 10).

Table-3
`D_1``D_2``D_3``D_4`SupplyRow Penalty (P)Total (T)P`xx`T
`S_1`19305010(7)0--109--
`S_2`703040609`20=60-40`200`4000=20xx200`
`S_3`408(8)702010`20=40-20`138`2760=20xx138`
Demand5077
Column
Penalty (P)
`30=70-40`--`30=70-40``40=60-20`
Total (T)1296816090
P`xx`T`3870=30xx129`--`4800=30xx160``3600=40xx90`


The lowest PT = 2760, occurs in row `S_3`.

The minimum `c_(ij)` in this row is `c_34` = 20.

The maximum allocation in this cell is min(10,7) = 7.
It satisfy demand of `D_4` and adjust the supply of `S_3` from 10 to 3 (10 - 7 = 3).

Table-4
`D_1``D_2``D_3``D_4`SupplyRow Penalty (P)Total (T)P`xx`T
`S_1`19305010(7)0--109--
`S_2`703040609`30=70-40`200`6000=30xx200`
`S_3`408(8)7020(7)3`30=70-40`138`4140=30xx138`
Demand5070
Column
Penalty (P)
`30=70-40`--`30=70-40`--
Total (T)1296816090
P`xx`T`3870=30xx129`--`4800=30xx160`--


The lowest PT = 3870, occurs in column `D_1`.

The minimum `c_(ij)` in this column is `c_31` = 40.

The maximum allocation in this cell is min(3,5) = 3.
It satisfy supply of `S_3` and adjust the demand of `D_1` from 5 to 2 (5 - 3 = 2).

Table-5
`D_1``D_2``D_3``D_4`SupplyRow Penalty (P)Total (T)P`xx`T
`S_1`19305010(7)0--109--
`S_2`703040609`30=70-40`200`6000=30xx200`
`S_3`40(3)8(8)7020(7)0--138--
Demand2070
Column
Penalty (P)
`70`--`40`--
Total (T)1296816090
P`xx`T`9030=70xx129`--`6400=40xx160`--


The lowest PT = 6000, occurs in row `S_2`.

The minimum `c_(ij)` in this row is `c_23` = 40.

The maximum allocation in this cell is min(9,7) = 7.
It satisfy demand of `D_3` and adjust the supply of `S_2` from 9 to 2 (9 - 7 = 2).

Table-6
`D_1``D_2``D_3``D_4`SupplyRow Penalty (P)Total (T)P`xx`T
`S_1`19305010(7)0--109--
`S_2`703040(7)602`70`200`14000=70xx200`
`S_3`40(3)8(8)7020(7)0--138--
Demand2000
Column
Penalty (P)
`70`------
Total (T)1296816090
P`xx`T`9030=70xx129`------


The lowest PT = 9030, occurs in column `D_1`.

The minimum `c_(ij)` in this column is `c_21` = 70.

The maximum allocation in this cell is min(2,2) = 2.
It satisfy supply of `S_2` and demand of `D_1`.


Initial feasible solution is
`D_1``D_2``D_3``D_4`SupplyRow Penalty (P)Total (T)P`xx`T
`S_1`19305010(7)7 9 | -- | -- | -- | -- | -- | 109 981 | -- | -- | -- | -- | -- |
`S_2`70(2)3040(7)60910 | 10 | 20 | 30 | 30 | 70 | 2002000 | 2000 | 4000 | 6000 | 6000 | 14000 |
`S_3`40(3)8(8)7020(7)1812 | 12 | 20 | 30 | -- | -- | 1381656 | 1656 | 2760 | 4140 | -- | -- |
Demand58714
Column
Penalty (P)
21
30
30
30
70
70
22
22
--
--
--
--
10
30
30
30
40
--
10
40
40
--
--
--
Total (T)1296816090
P`xx`T2709
3870
3870
3870
9030
9030
1496
1496
--
--
--
--
1600
4800
4800
4800
6400
--
900
3600
3600
--
--
--


The minimum total transportation cost `= 10 xx 7 + 70 xx 2 + 40 xx 7 + 40 xx 3 + 8 xx 8 + 20 xx 7 = 814`

Here, the number of allocated cells = 6 is equal to m + n - 1 = 3 + 4 - 1 = 6
`:.` This solution is non-degenerate


This material is intended as a summary. Use your textbook for detail explanation.
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6. Russell's approximation method
(Previous method)
2. Example-2
(Next example)





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