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If 7x₁ +4x2 840 is one of the problem constraints in a standard maximization problem in standard form with two decision variables, explain why the maximum value of the objective function exists Choose the correct answer *** OA. The constraint means that the feasible region is empty For any linear programming problem, if the feasible region is empty, then the maximum value of the objective function always exists OB. The constraint means that the feasible region is nonempty For any linear programming problem, if the feasible region is nonempty, the maximum value of the objective function always exists OC. The constraint means that the feasible region is bounded. For any linear programming problem, if the feasible region is bounded, then the maximum value of the objective function always exists OD. The constraint means that the feasible region is unbounded For any linear programming problem, if the feasible region is unbounded, then the maximum value of the objective function always exists.

If 7x₁ +4x2 840 is one of the problem constraints in a standard maximization problem in standard form with two decision variables, explain why the maximum value of the objective function exists Choose the correct answer *** OA. The constraint means that the feasible region is empty For any linear programming problem, if the feasible region is empty, then the maximum value of the objective function always exists OB. The constraint means that the feasible region is nonempty For any linear programming problem, if the feasible region is nonempty, the maximum value of the objective function always exists OC. The constraint means that the feasible region is bounded. For any linear programming problem, if the feasible region is bounded, then the maximum value of the objective function always exists OD. The constraint means that the feasible region is unbounded For any linear programming problem, if the feasible region is unbounded, then the maximum value of the objective function always exists.

Advanced Engineering Mathematics
Advanced Engineering Mathematics
10th Edition
ISBN:9780470458365
Author:Erwin Kreyszig
Publisher:Erwin Kreyszig
Chapter2: Second-order Linear Odes
Section: Chapter Questions
Problem 1RQ
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If 7x₁ +4x2 840 is one of the problem constraints in a standard maximization problem in standard form with two decision variables, explain why the maximum value of the objective function exists Choose the correct answer *** OA. The constraint means that the feasible region is empty For any linear programming problem, if the feasible region is empty, then the maximum value of the objective function always exists OB. The constraint means that the feasible region is nonempty For any linear programming problem, if the feasible region is nonempty, the maximum value of the objective function always exists OC. The constraint means that the feasible region is bounded. For any linear programming problem, if the feasible region is bounded, then the maximum value of the objective function always exists OD. The constraint means that the feasible region is unbounded. For any linear programming problem, if the feasible region is unbounded, then the maximum value of the objective function always exists.
Transcribed Image Text:If 7x₁ +4x2 840 is one of the problem constraints in a standard maximization problem in standard form with two decision variables, explain why the maximum value of the objective function exists Choose the correct answer *** OA. The constraint means that the feasible region is empty For any linear programming problem, if the feasible region is empty, then the maximum value of the objective function always exists OB. The constraint means that the feasible region is nonempty For any linear programming problem, if the feasible region is nonempty, the maximum value of the objective function always exists OC. The constraint means that the feasible region is bounded. For any linear programming problem, if the feasible region is bounded, then the maximum value of the objective function always exists OD. The constraint means that the feasible region is unbounded. For any linear programming problem, if the feasible region is unbounded, then the maximum value of the objective function always exists.
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