18. Linear mathematical programming techniques 20. Which of the following pairs of coordinates assume that all parameters in the models are: A. known with certainty represents a feasible solution for the inequalities 7x+3y 2 50 B. unknown 2x+5y 2 20? C. predictable D. unpredictable x, y 20 А. (7,1) В. (6,4) С. (3,8) D. (2,3) 19. The main purpose of using the non-negativity constraints in a linear mathematical model is to: A. Restrict the decision variables to negative values. B. Violates the constraints of the feasible solution. C. Restrict the decision variables to positive values. D. Does not violate any of the objective constraints.

Advanced Engineering Mathematics
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ISBN:9780470458365
Author:Erwin Kreyszig
Publisher:Erwin Kreyszig
Chapter2: Second-order Linear Odes
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Queueing Theory and Linear Programming

18. Linear mathematical programming techniques
assume that all parameters in the models are:
A. known with certainty
20. Which of the following pairs of coordinates
represents a feasible solution for the inequalities
7x +3y 2 50
B. unknown
C. predictable
D. unpredictable
2.x +5y 2 20?
x, y 20
А. (7,1)
В. (6,4)
С. (3,8)
D. (2,3)
19. The main purpose of using the non-negativity
constraints in a linear mathematical model is to:
A. Restrict the decision variables to negative
values.
B. Violates the constraints of the feasible
solution.
C. Restrict the decision variables to positive
values.
D. Does not violate any of the objective
constraints.
Transcribed Image Text:18. Linear mathematical programming techniques assume that all parameters in the models are: A. known with certainty 20. Which of the following pairs of coordinates represents a feasible solution for the inequalities 7x +3y 2 50 B. unknown C. predictable D. unpredictable 2.x +5y 2 20? x, y 20 А. (7,1) В. (6,4) С. (3,8) D. (2,3) 19. The main purpose of using the non-negativity constraints in a linear mathematical model is to: A. Restrict the decision variables to negative values. B. Violates the constraints of the feasible solution. C. Restrict the decision variables to positive values. D. Does not violate any of the objective constraints.
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