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Operations Research
MBA-024
ASSIGNMENT MODEL
UNIT II
• Suppose there are 5 machines and 5 jobs to be
performed.
• 1 machine can do only 1 job at a time.
• How the machines should be assigned to the
jobs?
• Given – the cost of performing a job on a
machine.
• An Assignment Problem (AP) is always square.
• The assignment is done on a one-to-one
matching basis.
• Only one allocation is possible in a given row or
column.
• The AP is inherently degenerate, as the
assignment is done on a one-to-one matching
basis. (In the above 5 machine 5 job problem,
there would be 25 cells, but allocation can be
made only in 5 cells, whereas 9 cells should be
allocated.)
• Total number of assignments possible = n!
Mathematical Formulation
Hungarian Method
Machine
X Y Z
Job
A 25 31 35
B 15 20 24
C 22 19 17
• Machine opportunity and job opportunity cost to
be determined.
• The minimum element of a particular row or
column to be subtracted from all elements of that
row or column.
Machine
X Y Z
Job
A 25 31 35
B 15 20 24
C 22 19 17
Machine
X Y Z
Job
A 25 31 35
B 15 20 24
C 22 19 17
Machine
X Y Z
Job
A 25-25 31-25 35-25
B 15-15 20-15 24-15
C 22-17 19-17 17-17
Machine
X Y Z
Job
A 0 6 10
B 0 5 9
C 5 2 0
Job Opportunity Cost
1st
Reduced Cost Matrix
Machine
X Y Z
Job
A 0 6 10
B 0 5 9
C 5 2 0
Machine
X Y Z
Job
A 0 4 10
B 0 3 9
C 5 0 0
Machine Opportunity Cost
2nd
Reduced Cost (Total Opportunity Cost) Matrix
0 4 10
0 3 9
5 0 0
• Optimal assignment is that
assignment where total
opportunity cost is zero.
• We draw horizontal and
vertical lines so as to cross
all the zero elements using
the minimum number of
lines.
0 4 10
0 3 9
5 0 0
• Optimal assignment is that
assignment where total
opportunity cost is zero.
• We draw horizontal and
vertical lines so as to cross
all the zero elements using
the minimum number of
lines.
• If the minimum number of lines required to do
so is equal to the number of rows or columns,
then optimum allocation is possible.
0 4 10
0 3 9
5 0 0
• Optimal assignment is that
assignment where total
opportunity cost is zero.
• We draw horizontal and
vertical lines so as to cross
all the zero elements using
the minimum number of
lines.
• If the minimum number of lines required to do
so is equal to the number of rows or columns,
then optimum allocation is possible.
• In this case it is not possible.
0 4 10
0 3 9
5 0 0
• We identify the minimum
element not covered by
lines.
0 4 10
0 3 9
5 0 0
• We identify the minimum
element not covered by
lines.
• In this case it is 3.
0 4 10
0 3 9
5 0 0
• We subtract it from…
Assignment Model: Applications
• Assign salespeople to sales territories.
• Assign vehicles to routes.
• Assign accountants to client accounts.
• Assign contracts to bidders through
systematic evaluation of bids from competing
suppliers.
• Assign naval vessels to patrol sectors.
• Schedule teachers to classes.
Assignment Model: Applications
• Matching men to machines according to
pieces produced per hour by each individual
on each machine.
• Matching teams to projects by the expected
cost of each team to accomplish each project.

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Unit ii-3-am

  • 3. • Suppose there are 5 machines and 5 jobs to be performed. • 1 machine can do only 1 job at a time. • How the machines should be assigned to the jobs? • Given – the cost of performing a job on a machine. • An Assignment Problem (AP) is always square. • The assignment is done on a one-to-one matching basis.
  • 4. • Only one allocation is possible in a given row or column. • The AP is inherently degenerate, as the assignment is done on a one-to-one matching basis. (In the above 5 machine 5 job problem, there would be 25 cells, but allocation can be made only in 5 cells, whereas 9 cells should be allocated.) • Total number of assignments possible = n!
  • 6. Hungarian Method Machine X Y Z Job A 25 31 35 B 15 20 24 C 22 19 17 • Machine opportunity and job opportunity cost to be determined. • The minimum element of a particular row or column to be subtracted from all elements of that row or column.
  • 7. Machine X Y Z Job A 25 31 35 B 15 20 24 C 22 19 17
  • 8. Machine X Y Z Job A 25 31 35 B 15 20 24 C 22 19 17
  • 9. Machine X Y Z Job A 25-25 31-25 35-25 B 15-15 20-15 24-15 C 22-17 19-17 17-17
  • 10. Machine X Y Z Job A 0 6 10 B 0 5 9 C 5 2 0 Job Opportunity Cost 1st Reduced Cost Matrix
  • 11. Machine X Y Z Job A 0 6 10 B 0 5 9 C 5 2 0
  • 12. Machine X Y Z Job A 0 4 10 B 0 3 9 C 5 0 0 Machine Opportunity Cost 2nd Reduced Cost (Total Opportunity Cost) Matrix
  • 13. 0 4 10 0 3 9 5 0 0 • Optimal assignment is that assignment where total opportunity cost is zero. • We draw horizontal and vertical lines so as to cross all the zero elements using the minimum number of lines.
  • 14. 0 4 10 0 3 9 5 0 0 • Optimal assignment is that assignment where total opportunity cost is zero. • We draw horizontal and vertical lines so as to cross all the zero elements using the minimum number of lines. • If the minimum number of lines required to do so is equal to the number of rows or columns, then optimum allocation is possible.
  • 15. 0 4 10 0 3 9 5 0 0 • Optimal assignment is that assignment where total opportunity cost is zero. • We draw horizontal and vertical lines so as to cross all the zero elements using the minimum number of lines. • If the minimum number of lines required to do so is equal to the number of rows or columns, then optimum allocation is possible. • In this case it is not possible.
  • 16. 0 4 10 0 3 9 5 0 0 • We identify the minimum element not covered by lines.
  • 17. 0 4 10 0 3 9 5 0 0 • We identify the minimum element not covered by lines. • In this case it is 3.
  • 18. 0 4 10 0 3 9 5 0 0 • We subtract it from…
  • 19. Assignment Model: Applications • Assign salespeople to sales territories. • Assign vehicles to routes. • Assign accountants to client accounts. • Assign contracts to bidders through systematic evaluation of bids from competing suppliers. • Assign naval vessels to patrol sectors. • Schedule teachers to classes.
  • 20. Assignment Model: Applications • Matching men to machines according to pieces produced per hour by each individual on each machine. • Matching teams to projects by the expected cost of each team to accomplish each project.