Answer: Scroll down for solution
Step-by-step explanation: To formulate this problem as a Linear Programming Problem (LPP), we need to define the decision variables, objective function, and constraints.
1. Decision Variables:
Let's denote the number of meters of suiting, shirting, and woolen produced as:
- x1: Number of meters of suiting produced
- x2: Number of meters of shirting produced
- x3: Number of meters of woolen produced
2. Objective Function:
The objective is to maximize the profit, which can be calculated as follows:
Profit = 2x1 + 4x2 + 3x3
3. Constraints:
a) Weaving Department:
The total run time available for weaving is 60 hours per week. The time required to produce 1 meter of suiting, shirting, and woolen in the weaving department is given as 3 minutes, 4 minutes, and 3 minutes, respectively. Since there are 60 minutes in an hour, the constraint for the weaving department can be expressed as:
3x1 + 4x2 + 3x3 ≤ 60
b) Processing Department:
The total run time available for processing is 40 hours per week. The time required to produce 1 meter of suiting, shirting, and woolen in the processing department is given as 2 minutes, 1 minute, and 3 minutes, respectively. The constraint for the processing department can be expressed as:
2x1 + 1x2 + 3x3 ≤ 40
c) Packing Department:
The total run time available for packing is 80 hours per week. The time required to produce 1 meter of suiting, shirting, and woolen in the packing department is given as 1 minute, 3 minutes, and 3 minutes, respectively. The constraint for the packing department can be expressed as:
1x1 + 3x2 + 3x3 ≤ 80
d) Non-negativity constraint:
The number of meters produced cannot be negative, so we have the constraint:
x1, x2, x3 ≥ 0
Now, we have the LPP formulated with the decision variables, objective function, and constraints. To find the solution, we can use a method such as the Simplex method or graphical method to optimize the objective function while satisfying the constraints.