A change in the right hand side of a constraint changes a. objective function coefficients b. other right hand sides c. the slope of the objective function d. the feasible region
A change in the right hand side of a constraint changes the feasible region.
So the correct answer is option d i.e. the feasible region.
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A change in the right hand side of a constraint changes a. objective function coefficients b....
Match the following terms to their definition Feasible region Binding constraint [Choose] [Choose A feasible solution for which there are no other feasible points with a better objective function value in the entire feasible region. The change in the optimal objective function value per unit increase in the right-hand side of a constraint Restrictions that limit the settings of the decision variables A controllable input for a linear programming model The expression that defines the quantity to be maximized or...
hapter 5 Quiz (pp. 150-162) Saved Help In linear programming, what-if analysis is associated with determining the effect of changing I. objective function coefficients Il. right-hand side values of constraints. IlI. decision variable values. 0150-13) Multiple Choice eBook objective function coefficients and right-hand side values of constraints References right-hand side values of constraints and decision variable values objective function coefficients, right-hand side values of constraints, and decision variable values objective function coefficients and decision veriable values None of the choices...
Define the followings: a. Sensitivity Analysis b. Sensitivity Analysis for Objective Function Coefficients c. Sensitivity Analysis for Right Hand Side Values d. Ranges of Optimality for Objective Function Coefficients e. Ranges of Feasibility for Right Hand Side Values f. Sensitivity Analysis by using QM for Windows g. Sensitivity Analysis by using Excel h. Shadow Price
Consider the following constraints and the c g graph below: Constraint L:4x-y21 Constraint 2: x+ys4 Constraint 3:-x-4y 2-8 x, y20 4x-y=1 x-4y -8 a. (2 points) Shade the feasible region in the graph provided above. b. (1 point) For this part only the objective function is Minimize -2x + y. Which of the following describes the optimal solution? (Put a check next to your answer) Infeasible solution Unique optimal solution the point (4,0) minimizes the LP Alternate optimal solution Unbounded...
(2 marks) Solve (find the optimal point and objective function value at the optimal point) the following optimisation problem min 2x+ y Subject to Obtain the gradient of both the objective function and constraint function at the optimal point. What condition do they meet at the optimal point? Suppose the right-hand side of the constraint equation is increased from 1 to 1.2. Without redoing the Lagrange multiplier method obtain an estimate for the change in objective function value. Verify using...
. Consider a Linear Programming (LP) problem with two decision variables. If the profit (cost) coefficient of one decision variable of the objective function is increased, then a. The feasible region will be increased b. There will be a redundant constraint c. The slope of the profit (cost) line will be changed d. The feasible region will be decreased e. None of the above
Find that right hand side is equal to left hand side Convert this code into python and then compare result If your left hand side is not equal to right hand side then find the error into your code values a = 2.0 b = 1.0 c = 2.0 d = 3.0 at the end print both left hand side and right hand side for example print lefthand print righthand a cadbc Adding Fractions : ^ bd
Figure 5 Constraint 2 Iso-profit line (objective function) 3 2 А B 4 x2 с 1 6 Constraint 1 5 D E x1 24. For a problem with the same constraints as in figure 5 but a different objective function, it was found that the optimal solution was at point A. At point A, which constraint or constraints are binding? Select all that apply. a. X1 >=0 b. x2 >=0 C. Constraint 1 d. Constraint 2
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