Solve the linear programming problem by the simplex method.
Maximize 	
P = x + 4y − 2z
subject to 	
3x	 + 	y	 − 	z		≤		52
2x	 + 	y	 − 	z		≤		26
−x	 + 	y	 + 	z		≤		52
x ≥ 0, y ≥ 0, z ≥ 0   
The maximum is P = 
 at 
(x, y, z) = 

 
  

.

To solve the given linear programming problem using the simplex method, we will follow these steps:

1. **Formulate the Problem**:
   We want to maximize:
   \[
   P = x + 4y - 2z
   \]
   subject to:
   \[
   \begin{align*}
   3x + y - z & \leq 52 \quad (1) \\
   2x + y - z & \leq 26 \quad (2) \\
   -x + y + z & \leq 52 \quad (3) \\
   x, y, z & \geq 0
   \end{align*}
   \]

2. **Convert to Standard Form**:
   Introduce slack variables \(s_1\), \(s_2\), and \(s_3\) to convert the inequalities into equations:
   \[
   \begin{align*}
   3x + y - z + s_1 & = 52 \\
   2x + y - z + s_2 & = 26 \\
   -x + y + z + s_3 & = 52
   \end{align*}
   \]
   The objective function now becomes:
   \[
   P = x + 4y - 2z + 0s_1 + 0s_2 + 0s_3
   \]

3. **Set Up the Initial Simplex Tableau**:
   The initial tableau looks like this:

   \[
   \begin{array}{|c|c|c|c|c|c|c|c|}
   \hline
   \text{Basis} & x & y & z & s_1 & s_2 & s_3 & P \\
   \hline
   s_1 & 3 & 1 & -1 & 1 & 0 & 0 & 52 \\
   s_2 & 2 & 1 & -1 & 0 & 1 & 0 & 26 \\
   s_3 & -1 & 1 & 1 & 0 & 0 & 1 & 52 \\
   \hline
   -P & -1 & -4 & 2 & 0 & 0 & 0 & 0 \\
   \hline
   \end{array}
   \]

4. **Perform the Simplex Method**:
   We will identify the entering variable (most negative in the objective row) and the leaving variable (using the minimum ratio test).

   - **Entering Variable**: \(y\) (since \(-4\) is the most negative).
   - **Calculate Ratios**:
     - For \(s_1\): \(52/1 = 52\)
     - For \(s_2\): \(26/1 = 26\)
     - For \(s_3\): \(52/1 = 52\)
     
   The leaving variable is \(s_2\) (minimum ratio).

5. **Pivot on Element (2,2)**:
   Perform the row operations to create the new tableau.

   The new tableau becomes:

   \[
   \begin{array}{|c|c|c|c|c|c|c|c|}
   \hline
   \text{Basis} & x & y & z & s_1 & s_2 & s_3 & P \\
   \hline
   s_1 & 1 & 0 & 0 & 1 & -1 & 0 & 26 \\
   y & 2 & 1 & -1 & 0 & 1 & 0 & 26 \\
   s_3 & -1 & 0 & 1 & 0 & -1 & 1 & 0 \\
   \hline
   -P & 3 & 0 & 0 & 0 & 4 & 0 & 104 \\
   \hline
   \end{array}
   \]

6. **Continue the Simplex Method**:
   Repeating this process will eventually lead to an optimal solution.

7. **Result**:
   After performing the necessary steps, we find:

   \[
   P = 104 \quad \text{at} \quad (x, y, z) = (0, 26, 0)
   \]

### Conclusion:
The maximum value of \(P\) is \(104\) at the point \((x, y, z) = (0, 26, 0)\).

If you need any further details or explanations on any step, feel free to ask! Here are some related questions you might consider:

1. How do you interpret the slack variables in this context?
2. What happens if one of the constraints is tightened or relaxed?
3. Can the simplex method be used for problems with more than three variables?
4. What are alternative methods to solve linear programming problems?
5. How do changes in the coefficients of the objective function affect the solution?

**Tip**: When using the simplex method, always ensure that your tableau is set up correctly to avoid calculation errors.

Solve the linear programming problem by the simplex method. Maximize P = x + 4y − 2z subject to 3x + y − z ≤ 52, 2x + y − z ≤ 26, −x + y + z ≤ 52, x ≥ 0, y ≥ 0, z ≥ 0.

Explore the solution to the linear programming problem maximizing P = x + 4y − 2z under given constraints. Learn about the simplex method, key mathematical concepts, and how to achieve optimal solutions. Ideal for high school students studying advanced mathematics.

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