Linear Programming Problem Set 1
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This set of Business Mathematics Multiple Choice Questions & Answers (MCQs) focuses on Linear Programming Problem Set 1
Q1 | Operation research analysis does not
- predict future operation
- build more than one model
- collect the relevant data
- recommended decision and accept
Q2 | A constraint in an LP model restricts
- value of the objective function
- value of the decision variable
- use of the available resourses
- all of the above
Q3 | A feasible solution of LPP
- must satisfy all the constraints simultaneously
- need not satisfy all the constraints, only some of them
- must be a corner point of the feasible region
- all of the above
Q4 | Maximization of objective function in LPP means
- value occurs at allowable set decision
- highest value is chosen among allowable decision
- none of the above
- all of the above
Q5 | Alternative solution exist in a linear programming problem when
- one of the constraint is redundant
- objective function is parallel to one of the constraints
- two constraints are parallel
- all of the above
Q6 | The linear function of the variables which is to be maximize or minimize is called
- constraints
- objective function
- decision variable
- none of the above
Q7 | The true statement for the graph of inequations 3x+2y≤6 and 6x+4y≥20 , is
- both graphs are disjoint
- both do not contain origin
- both contain point (1, 1)
- none of these
Q8 | The value of objective function is maximum under linear constraints
- at the center of feasible region
- at (0,0)
- at any vertex of feasible region
- the vertex which is at maximum distance from (0, 0)
Q9 | A model is
- an essence of reality
- an approximation
- an idealization
- all of the above
Q10 | The first step in formulating a linear programming problem is
- identify any upper or lower bound on the decision variables
- state the constraints as linear combinations of the decision variables
- understand the problem
- identify the decision variables
Q11 | Constraints in an LP model represents
- limititations
- requirements
- balancing, limitations and requirements
- all of above
Q12 | The best use of linear programming is to find optimal use of
- money
- manpower
- machine
- all the above
Q13 | Which of the following is assumption of an LP model
- divisibility
- proportionality
- additivity
- all of the above
Q14 | Before formulating a formal LP model, it is better to
- express each constraints in words
- express the objective function in words
- verbally identify decision variables
- all of the above
Q15 | Non-negative condition in an LP model implies
- a positive coefficient of variables in objective function
- a positive coefficient of variables in any constraint
- non-negative value of resourse
- none of the above
Q16 | The set of decision variable which satisfies all the constraints of the LPP is called as-----
- solution
- basic solution
- feasible solution
- none of the above
Q17 | The intermediate solutions of constraints must be checked by substituting them back into
- objective function
- constraint equations
- not required
- none of the above
Q18 | A basic solution is called non-degenerate, if
- all the basic variables are zero
- none of the basic variables is zero
- at least one of the basic variables is zero
- none of these
Q19 | The graph of x≤2 and y≥2 will be situated in the
- first and second quadrant
- second and third quadrant
- first and third quadrant
- third and fourth quadrant
Q20 | A solution which satisfies non-negative conditions also is called as-----
- solution
- basic solution
- feasible solution
- none of the above
Q21 | In graphical method of linear programming problem if the iOS-cost line coincide with a sideof region of basic feasible solutions we get
- unique optimum solution
- unbounded optimum solution
- no feasible solution
- infinite number of optimum solutions
Q22 | The objective function for a L.P model is 3𝑥1 + 2𝑥2, if 𝑥1 = 20 and 𝑥2 = 30, what is the valueof the objective function?
- 0
- 50
- 60
- 120
Q23 | If the value of the objective function 𝒛 can be increased or decreased indefinitely, suchsolution is called
- bounded solution
- unbounded solution
- solution
- none of the above
Q24 | For the constraint of a linear optimizing function z=x1+x2 given by x1+x2≤1, 3x1+x2≥3 andx1, x2≥0
- there are two feasible regions
- there are infinite feasible regions
- there is no feasible region
- none of these
Q25 | If the number of available constraints is 3 and the number of parameters to be optimized is 4,then
- the objective function can be optimized
- the constraints are short in number
- the solution is problem oriented
- none of these