Question
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Given constraints:

Explain the steps for maximizing the objective
function .

Ask by Carroll Chan. in the United States
Mar 22,2025

Upstudy AI Solution

Tutor-Verified Answer

Answer

To maximize with the constraints , , , and , evaluate at the vertices , , , and . The maximum value of is 32 at .

Solution

Step 1. Write Down the Constraints and Objective Function
We are given the constraints:
and the objective function to maximize is
Step 2. Simplify the Constraints
Divide the inequality by 2 to obtain:
Thus, the constraints become:
Step 3. Identify the Feasible Region
The constraints and restrict the solution to the first quadrant. The inequalities
describe two parallel lines. The feasible region is the set of points in the first quadrant that lie between (or on) the lines:
Step 4. Determine the Corner Points (Vertices) of the Feasible Region
Find the intersections of the constraint boundaries:
  1. Intersection of and :
  2. Intersection of and :
  3. Intersection of and :
  4. Intersection of and :
Thus, the vertices of the feasible region are:
Step 5. Evaluate the Objective Function at Each Vertex
Substitute each vertex into the objective function :
  1. At :
  2. At :
  3. At :
  4. At :
Step 6. Determine the Maximum Value
Among the calculated values, the maximum value is:
Conclusion
The objective function is maximized at with a maximum value of

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The Deep Dive

To solve this linear programming problem and maximize the objective function under the given constraints, follow these steps:
  1. Identify the Feasible Region: Start by graphing the constraints. Convert them into equalities:
    • For , rearranging gives .
    • For , rearranging gives .
    • Also, remember the non-negativity constraints and .
  2. Plot the Constraints: Draw the lines representing and on a graph along with the axes. Shade the feasible region where all constraints overlap.
  3. Find the Vertices of the Feasible Region: Identify the intersection points (vertices) of the lines you’ve drawn. These vertices are potential candidates for maximizing . The corners will typically be:
    • Intersection of and the axes.
    • Intersection of and the or axis.
    • The intersection of the two lines.
  4. Evaluate the Objective Function at Each Vertex: Plug in the coordinates of each vertex into the objective function to find which gives the maximum value.
  5. Select the Maximum Value: The vertex that yields the highest value of from the previous step is the solution to your linear programming problem.
Enjoy solving linear programming problems—they are like puzzles that unlock the secrets of optimization!

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