Math Problem Statement

Angel Furniture Shop manufactures tables and chairs. All tables and chairs pass through two departments, namely, Department 1 and Department 2. In one production period, Department 1 and Department 2 have a total of 120 and 96 available hours, respectively. Producing one table requires 5 hours in Department 1 and 4 hours in Department 2. Similarly, producing one chair requires 6 hours in Department 1 and 3 hours in Department 2. The contribution margin or profit of a table is ₱30.00 per unit and a chair is ₱24.00 per unit. Required: Using the graphical method, perform the following: 1. Formulate the objective function. 2. Formulate the constraints. 3. Prepare a graph. 4. Determine the feasible region and shade it in the graph. 5. Formulate a decision.

Solution

The problem provided involves linear programming for optimizing the production of tables and chairs at Angel Furniture Shop. Here's how we can tackle each of the requested tasks step by step:

Problem Summary:

  • Departments: There are two departments (Department 1 and Department 2).
  • Available Hours: Department 1 has 120 hours and Department 2 has 96 hours available for one production period.
  • Production Time:
    • Producing one table requires 5 hours in Department 1 and 4 hours in Department 2.
    • Producing one chair requires 6 hours in Department 1 and 3 hours in Department 2.
  • Profit:
    • Profit for one table: ₱30.00
    • Profit for one chair: ₱24.00

Required Tasks:

  1. Formulate the objective function.
  2. Formulate the constraints.
  3. Prepare a graph.
  4. Determine the feasible region and shade it in the graph.
  5. Formulate a decision.

Step 1: Formulate the Objective Function

The objective is to maximize profit, which is the sum of profits from tables and chairs. Let:

  • xx = number of tables produced
  • yy = number of chairs produced

The profit function (Objective Function) is: Maximize Z=30x+24y\text{Maximize } Z = 30x + 24y Where ZZ represents the total profit.

Step 2: Formulate the Constraints

The constraints arise from the limited hours available in each department.

  • Department 1 Constraint:

    • Producing one table takes 5 hours, and one chair takes 6 hours.
    • Total hours available in Department 1: 120 hours. 5x+6y1205x + 6y \leq 120
  • Department 2 Constraint:

    • Producing one table takes 4 hours, and one chair takes 3 hours.
    • Total hours available in Department 2: 96 hours. 4x+3y964x + 3y \leq 96
  • Non-negativity constraints: x0andy0x \geq 0 \quad \text{and} \quad y \geq 0

Step 3: Prepare a Graph

To graph these inequalities, we'll plot the lines corresponding to the constraints:

  1. 5x+6y=1205x + 6y = 120
  2. 4x+3y=964x + 3y = 96

We will find the intercepts for these lines, and then draw the lines on a graph to determine the feasible region.

  • For 5x+6y=1205x + 6y = 120:

    • xx-intercept: Set y=0y = 0, then 5x=1205x = 120, so x=24x = 24.
    • yy-intercept: Set x=0x = 0, then 6y=1206y = 120, so y=20y = 20.
  • For 4x+3y=964x + 3y = 96:

    • xx-intercept: Set y=0y = 0, then 4x=964x = 96, so x=24x = 24.
    • yy-intercept: Set x=0x = 0, then 3y=963y = 96, so y=32y = 32.

Step 4: Determine the Feasible Region

The feasible region is the area of the graph where all the constraints overlap. We need to find the intersection points of the lines and shade the region that satisfies all the inequalities.

Step 5: Formulate a Decision

After identifying the feasible region, the next step is to find the point in this region that maximizes the objective function Z=30x+24yZ = 30x + 24y. This can be done by evaluating ZZ at the vertices (corner points) of the feasible region.

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Math Problem Analysis

Mathematical Concepts

Linear Programming
Optimization
Graphing Systems of Inequalities

Formulas

Objective function: Max Z = 30x + 24y
Department 1 constraint: 5x + 6y <= 120
Department 2 constraint: 4x + 3y <= 96
Non-negativity constraint: x >= 0, y >= 0

Theorems

Feasible Region Theorem
Corner Point Theorem

Suitable Grade Level

Undergraduate (Operations Research, Business Mathematics)