Math Problem Statement

linear programming problem (LPP) to maximize the objective function using simplex method for the following objective function

Z = 5x + 4y

Subject to the following constraints:

3x + 5y ≤ 78 4x + y ≤ 36 x, y ≥ 0

Solution

To solve the given Linear Programming Problem (LPP) using the Simplex Method, we need to formulate the problem and solve it step by step. Here's the detailed approach:

Objective Function

Maximize Z=5x+4yZ = 5x + 4y

Constraints

  1. 3x+5y783x + 5y \leq 78
  2. 4x+y364x + y \leq 36
  3. x,y0x, y \geq 0

Step 1: Convert Inequalities to Equalities (Slack Variables)

Introduce slack variables s1s_1 and s2s_2 to convert the inequalities into equalities:

  1. 3x+5y+s1=783x + 5y + s_1 = 78
  2. 4x+y+s2=364x + y + s_2 = 36

Slack variables s1,s20s_1, s_2 \geq 0.

Step 2: Initial Simplex Table

We write the initial simplex table using the augmented form of the constraints and objective function:

Basic Variablexxyys1s_1s2s_2RHS
s1s_1351078
s2s_2410136
ZZ-5-4000

Step 3: Identify Entering and Leaving Variables

  • The entering variable is the one with the most negative coefficient in the objective function row (ZZ). Here, xx (coefficient = -5) is the entering variable.
  • Calculate the pivot row using the formula RHS/Coefficient of entering variable\text{RHS} / \text{Coefficient of entering variable}:
    • For s1s_1: 78/3=2678 / 3 = 26
    • For s2s_2: 36/4=936 / 4 = 9

The pivot row is for s2s_2, as it has the smallest ratio.

Step 4: Perform Row Operations

Using the pivot element (4 in the s2s_2 row under xx), perform row operations to make the pivot column unitary and update the table.

New Simplex Table:

After row operations, the updated table becomes:

Basic Variablexxyys1s_1s2s_2RHS
s1s_1011/41-3/445
xx11/401/49
ZZ0-3/405/445

Step 5: Repeat Process

  • The next entering variable is yy (most negative coefficient in the ZZ row, 3/4-3/4).
  • Compute pivot row again:
    • For s1s_1: 45/(11/4)=16.3645 / (11/4) = 16.36
    • For xx: 9/(1/4)=369 / (1/4) = 36

The pivot row is for s1s_1.

Perform operations to update the table:

Final table:

Basic Variablexxyys1s_1s2s_2RHS
yy014/11-3/1116.36
xx10-1/117/117.64
ZZ001/111/1158.18

Step 6: Optimal Solution

From the final table:

  • x=7.64x = 7.64
  • y=16.36y = 16.36
  • Maximum Z=58.18Z = 58.18

Summary

The optimal solution is:

  • x=7.64x = 7.64, y=16.36y = 16.36
  • Maximum Z=58.18Z = 58.18

Would you like a step-by-step explanation of any part, or assistance with graphing? Here are five related questions:

  1. How can the graphical method validate this solution?
  2. What happens if an additional constraint is added?
  3. Can this problem be solved using Python or Excel Solver?
  4. How does the simplex method handle unbounded solutions?
  5. What are the limitations of using slack variables?

Tip: Always double-check the pivot element and row operations to ensure accuracy in simplex calculations

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Math Problem Analysis

Mathematical Concepts

Linear Programming
Simplex Method
Optimization

Formulas

Objective function Z = 5x + 4y
Slack variables: s1, s2
Pivot element calculation: RHS / coefficient of entering variable

Theorems

Simplex Method Algorithm

Suitable Grade Level

Grades 11-12, College Level