Exam 17: LP: Simplex Method
Exam 1: Introduction30 Questions
Exam 2: Introduction to Linear Programming28 Questions
Exam 3: LP Sensitivity Analysis and Interpretation of Solution31 Questions
Exam 4: Linear Programming Applications21 Questions
Exam 5: Advanced Linear Programming Applications24 Questions
Exam 6: Distribution and Network Problems31 Questions
Exam 7: Integer Linear Programming30 Questions
Exam 8: Nonlinear Optimization Models33 Questions
Exam 9: Project Scheduling: Pertcpm32 Questions
Exam 10: Inventory Models33 Questions
Exam 11: Waiting Line Models33 Questions
Exam 12: Simulation33 Questions
Exam 13: Decision Analysis24 Questions
Exam 14: Multicriteria Decisions30 Questions
Exam 15: Forecasting34 Questions
Exam 16: Markov Processes25 Questions
Exam 17: LP: Simplex Method29 Questions
Exam 18: Simplex-Based Sensitivity Analysis and Duality20 Questions
Exam 19: Solution Procedures for Transportation and Assignment Problems23 Questions
Exam 20: Minimal Spanning Tree12 Questions
Exam 21: Dynamic Programming19 Questions
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We recognize infeasibility when one or more of the artificial variables do not remain in the solution at a positive value.
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Correct Answer:
False
Infeasibility exists when one or more of the artificial variables
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Correct Answer:
B
Which of the following is not a step that is necessary to prepare a linear programming problem for solution using the simplex method?
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Correct Answer:
C
When a set of simultaneous equations has more variables than constraints,
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The variable to enter into the basis is the variable with the largest positive cj - zj value.
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When a system of simultaneous equations has more variables than equations, there is a unique solution.
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Every extreme point of the graph of a two variable linear programming problem is a basic feasible solution.
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A basic feasible solution satisfies the nonnegativity restriction.
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An alternative optimal solution is indicated when in the simplex tableau
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A minimization problem with four decision variables, two greater-than-or-equal-to constraints, and one equality constraint will have
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In the simplex method, a tableau is optimal only if all the cj - zj values are
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To determine a basic solution set of n-m, the variables equal to zero and solve the m linear constraint equations for the remaining m variables.
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When there is a tie between two or more variables for removal from the simplex tableau,
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At each iteration of the simplex procedure, a new variable becomes basic and a currently basic variable becomes nonbasic, preserving the same number of basic variables and improving the value of the objective function.
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The variable to remove from the current basis is the variable with the smallest positive cj - zj value.
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