2.2. Solve the following linear programs using the simplex method. If the problem is two dimensional, graph the feasible region, and outline the progress of the algorithm. (ii) maximize z = 5x1 +3x2 + 2x3 subject to 4x1 + 5x2 + 2xz + x4 < 20 3x1 + 4x2 – x3 + x4 < 30 X1, X2, X3, X4 > 0.

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ChapterP: Prerequisites: Fundamental Concepts Of Algebra
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**Problem 2.2: Solving Linear Programs Using the Simplex Method**

The task is to solve the following linear programming problem using the simplex method. For problems that are two-dimensional, graph the feasible region and outline the progress of the algorithm.

**Problem (ii)**

**Objective Function:**
Maximize \( z = 5x_1 + 3x_2 + 2x_3 \)

**Subject to Constraints:**

1. \( 4x_1 + 5x_2 + 2x_3 + x_4 \leq 20 \)
2. \( 3x_1 + 4x_2 - x_3 + x_4 \leq 30 \)
3. \( x_1, x_2, x_3, x_4 \geq 0 \)

**Explanation:**

- The objective is to find values for \( x_1, x_2, x_3, \) and \( x_4 \) that maximize the function \( z \) while satisfying the given inequality constraints.
- Each constraint represents a half-space in the variable space, and the intersection of these half-spaces forms the feasible region.
- The simplex method is an iterative algorithm used to navigate the vertices of the feasible region to find the optimal value for the objective function.
- Ensure that all variables are non-negative as per the non-negativity constraint. 

If this problem were two-dimensional, the feasible region would be graphed, and the progress of the simplex algorithm would be depicted by showing the movement from vertex to vertex until the optimal solution is reached. However, with four variables, this visualization is not applicable directly.
Transcribed Image Text:**Problem 2.2: Solving Linear Programs Using the Simplex Method** The task is to solve the following linear programming problem using the simplex method. For problems that are two-dimensional, graph the feasible region and outline the progress of the algorithm. **Problem (ii)** **Objective Function:** Maximize \( z = 5x_1 + 3x_2 + 2x_3 \) **Subject to Constraints:** 1. \( 4x_1 + 5x_2 + 2x_3 + x_4 \leq 20 \) 2. \( 3x_1 + 4x_2 - x_3 + x_4 \leq 30 \) 3. \( x_1, x_2, x_3, x_4 \geq 0 \) **Explanation:** - The objective is to find values for \( x_1, x_2, x_3, \) and \( x_4 \) that maximize the function \( z \) while satisfying the given inequality constraints. - Each constraint represents a half-space in the variable space, and the intersection of these half-spaces forms the feasible region. - The simplex method is an iterative algorithm used to navigate the vertices of the feasible region to find the optimal value for the objective function. - Ensure that all variables are non-negative as per the non-negativity constraint. If this problem were two-dimensional, the feasible region would be graphed, and the progress of the simplex algorithm would be depicted by showing the movement from vertex to vertex until the optimal solution is reached. However, with four variables, this visualization is not applicable directly.
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