Ops Ch 5 T/F
T/F: A conditional constraint specifies the conditions under which variables are integers or real variables.
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T/F: Rounding non-integer solution values up to the nearest integer value will result in an infeasible solution to an integer linear programming problem.
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T/F: In a 0-1 integer model, the solution values of the decision variables are 0 or 1.
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T/F: If we are solving a 0-1 integer programming problem, the constraint x1 + x2 = 1 is a mutually exclusive constraint.
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T/F: If we are solving a 0-1 integer programming problem, the constraint x1 = x2 is a conditional constraint.
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T/F: If we are solving a 0-1 integer programming problem, the constraint x1 ≤ x2 is a mutually exclusive constraint.
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T/F: In a 0-1 integer programming problem involving a capital budgeting application (where xj = 1, if project j is selected, xj = 0, otherwise) the constraint x1 - x2 ≤ 0 implies that if project 2 is selected, project 1 cannot be selected.
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T/F: In a mixed integer model, all decision variables have integer solution values.
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T/F: In a mixed integer model, the solution values of the decision variables are 0 or 1.
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T/F: In the classic game showPassword, the suave, silver-haired host informed the contestants, "you can choose to pass or to play." This expression suggests a mixed integer model is most appropriate.
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T/F: The branch and bound solution method cannot be applied to 0-1 integer programming problems.
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T/F: The management scientist's fiance informed him that if they were to be married, he would also have to welcome her mother into their home. The management scientist should model this decision as a contingency constraint.
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T/F: A feasible solution to an integer programming problem is ensured by rounding down non-integer solution values.
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T/F: If we are solving a 0-1 integer programming problem, the constraint x1 + x2 ≤ 1 is a mutually exclusive constraint.
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T/F: If we are solving a 0-1 integer programming problem, the constraint x1 ≤ x2 is a conditional constraint.
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T/F: In a mixed integer model, some solution values for decision variables are integer and others can be non-integer.
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T/F: In a problem involving capital budgeting applications, the 0-1 variables designate the acceptance or rejection of the different projects.
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T/F: In a total integer model, all decision variables have integer solution values.
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T/F: One type of constraint in an integer program is a multiple-choice constraint.
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T/F: Rounding non-integer solution values up to the nearest integer value can result in an infeasible solution to an integer programming problem.
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T/F: The college dean is deciding among three equally qualified candidates for his associate dean position. If this situation can be modeled as an integer program, the decision variables would be cast as 0-1 integer variables.
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T/F: The divisibility assumption is violated by integer programming.
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T/F: The production planner for Airbus showed his boss the latest product mix suggestion from their slick new linear programming model: 12.5 model 320s and 17.4 model 340s. The boss looked over his glasses at the production planner and reminded him that they had several half airplanes from last year's production rusting in the parking lot. No one, it seems, is interested in half of an airplane. The production planner whipped out his red pen and crossed out the .5 and .4, turning the new plan into 12 model 320s and 17 model 340s. This production plan is definitely feasible.
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T/F: The three types of integer programming models are total, 0-01, and mixed.
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