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# MTH601-Operations Research Quiz MCQs Lecture 23-45 Finalterm Objective Questions

MTH601-Operations Research Quiz MCQS #Objective #Questions #FinalTerm
1. The North-West Corner Rule
• is based on the concept of minimizing opportunity cost
• is used to find optimal solution
• is used to find an initial feasible solution ✔
• None
2. In the initial iteration of Big M-method, the artificial variables appear in ___
• Basis ✔
• Non-basic variables set
3. In the Simplex method to solve an LP problem, Gauss Jordan Elimination method demands that all the key column’s entries should be ___
• strictly positive
• strictly negative
• maximum or minimum
• zero ✔
4. In North West Corner method, in the first row and first column, available resource and sink contain ‘5’ and ‘7’ units respectively; then which of the following amount ‘x11’ will be allocated in the cell(1, 1)?
• Average(5,7) = 6
• Max(5,7) = 7 ✔
• Min(5,7) = 5
• Min(5,7-5) = 2
5. In M-method, which of the following is true about the coefficient (M) of artificial variable (A) in the objective function?
• M–>Zero ✔
• M–>+infinity
• M–>-infinity
• M–>optimal solution
6. If a variable in the Primal is unrestricted in sign, then the corresponding constraint in the dual will be of ___ type and vice versa.
• >=
• <=
• = ✔
• None
7. In Simplex Standard table to solve an LP problem, if the ratio by taking the RHS of each row and dividing by the corresponding element of the key column is {2/3, 1/3, -1/2}, then which of the following variable will be leaving?
• Variable corresponding to ‘2/3’
• Variable corresponding to ‘5’
• Variable corresponding to ‘1/3’
• Variable corresponding to ‘-1/2’ ✔
8. While facing degeneracy in solving an LP problem, then the further iterations always assure the non-negative optimal solution.
• True
• False ✔
9. The dual of the dual of a Linear Programming problem is itself the ___ problem.
• Primal ✔
• dual
• assignment
• transportation
10. In two phase method process, first phase ___ the sum of artificial variables.
• minimize ✔
• maximize
• maximize or minimize depending on the situation
• None

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