4. Reconsider the model in Problem 3 with objective function Maximize Z = C₁x₁ + ₂x₂, where C₁ ≥ 0, C₂ ≥ 0. Use the sensitivity analysis on the objective coefficients to answer the following questions. (a) Find the range of such that the optimal solution remains as (x₁, x₂) = (3,4). C₁ (b) Find the range of such that the optimal solution remains as (x₁,x₂) = (4,2). C₂ (c) Find the range of such that the optimal solution remains as (x₁, x₂) = (0,5). (d) If c₁ and c₂ are allowed to be negative, find the conditions on c₁ and C₂, and the range of such that the optimal solution remains as (x₁, x₂) = (4,0). C₂ Question 3 is given as follows: 3. Consider the following problem. Maximize Z = 3x₁ + 2x₂, subject to X1 ≤4 x₁ + 3x₂ ≤ 15 2x₁ + x₂ ≤ 10 (resource 1) (resource 2) (resource 3) and x₁ ≥ 0, x₂ ≥ 0, x3 ≥ 0. The optimal solution is (x₁, x₂) = (3,4) with Z* = 17. (a) Is any of these three constraints binding constraint? (b) Use graphical analysis to determine the shadow prices for the respective resources. 3

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### Sensitivity Analysis and Optimization Problem

#### Problem 4

Reconsider the model from Problem 3 with the objective function:

\[
\text{Maximize } Z = c_1 x_1 + c_2 x_2
\]

where \( c_1 \geq 0, c_2 \geq 0 \). Use sensitivity analysis on the objective coefficients to answer the following questions:

(a) Find the range of \(\frac{c_1}{c_2}\) such that the optimal solution remains as \((x_1^*, x_2^*) = (3,4)\).

(b) Find the range of \(\frac{c_1}{c_2}\) such that the optimal solution remains as \((x_1^*, x_2^*) = (4,2)\).

(c) Find the range of \(\frac{c_1}{c_2}\) such that the optimal solution remains as \((x_1^*, x_2^*) = (0,5)\).

(d) If \( c_1 \) and \( c_2 \) are allowed to be negative, find the conditions on \( c_1 \) and \( c_2 \), and the range of \(\frac{c_1}{c_2}\) such that the optimal solution remains as \((x_1^*, x_2^*) = (4,0)\).

#### Question 3

Given as follows:

Consider the following problem:

\[
\text{Maximize } Z = 3x_1 + 2x_2,
\]

subject to:

- \( x_1 \leq 4 \) (resource 1)
- \( x_1 + 3x_2 \leq 15 \) (resource 2)
- \( 2x_1 + x_2 \leq 10 \) (resource 3)
- \( x_1 \geq 0, \, x_2 \geq 0, \, x_3 \geq 0 \).

The optimal solution is \((x_1^*, x_2^*) = (3,4)\) with \( Z^* = 17 \).

(a) Is any of these three constraints a binding constraint?

(b) Use graphical analysis to determine the shadow prices for the respective resources
Transcribed Image Text:### Sensitivity Analysis and Optimization Problem #### Problem 4 Reconsider the model from Problem 3 with the objective function: \[ \text{Maximize } Z = c_1 x_1 + c_2 x_2 \] where \( c_1 \geq 0, c_2 \geq 0 \). Use sensitivity analysis on the objective coefficients to answer the following questions: (a) Find the range of \(\frac{c_1}{c_2}\) such that the optimal solution remains as \((x_1^*, x_2^*) = (3,4)\). (b) Find the range of \(\frac{c_1}{c_2}\) such that the optimal solution remains as \((x_1^*, x_2^*) = (4,2)\). (c) Find the range of \(\frac{c_1}{c_2}\) such that the optimal solution remains as \((x_1^*, x_2^*) = (0,5)\). (d) If \( c_1 \) and \( c_2 \) are allowed to be negative, find the conditions on \( c_1 \) and \( c_2 \), and the range of \(\frac{c_1}{c_2}\) such that the optimal solution remains as \((x_1^*, x_2^*) = (4,0)\). #### Question 3 Given as follows: Consider the following problem: \[ \text{Maximize } Z = 3x_1 + 2x_2, \] subject to: - \( x_1 \leq 4 \) (resource 1) - \( x_1 + 3x_2 \leq 15 \) (resource 2) - \( 2x_1 + x_2 \leq 10 \) (resource 3) - \( x_1 \geq 0, \, x_2 \geq 0, \, x_3 \geq 0 \). The optimal solution is \((x_1^*, x_2^*) = (3,4)\) with \( Z^* = 17 \). (a) Is any of these three constraints a binding constraint? (b) Use graphical analysis to determine the shadow prices for the respective resources
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