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    Graphical solution - Objective function coefficient

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    Use a graph to illustrate why a change in an objective function coefficient does not necessarily lead to a change in the optimal values of the decision variables, but a change in the right-hand sides of a binding constraint does lead to new values.

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    https://brainmass.com/math/graphs-and-functions/graphical-solution-objective-function-coefficient-172747

    Solution Preview

    Use a graph to illustrate why a change in an objective function coefficient does not necessarily lead to a change in the optimal values of the decision variables, but a change in the right-hand sides of a binding constraint does lead to new values.
    This condition can be explained by following example:
    Objective function: Maximize Z= $400C + $100T
    Subject to constraints:
    8C+10T<= 80
    2C +6T<=36
    C<=6
    C,T >= 0
    CHANGE IN OBJECTIVE FUNCTION CO_EFFICIENT:
    Following graph shows the graphical solution to above problem. The shaded region represents feasibility area for the problem. Optimal solution: C=6, T=3.2, Z=$2720

    The shaded are shows the feasibility region and the pink line shows ...

    Solution Summary

    This solution provides details on why a change in an objective function coefficient does not necessarily lead to a change in the optimal values of the decision variables

    $2.19

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