Using linear programming, the factory should manufacture 200 chairs, 150 tables, and 50 bookcases to maximize the profit.
Forming the linear programming objective and constraints functions:
Cutting Assembly Finishing Profits
Maximum operating hours 600 500 300
Chair requirements 1 1 1 $20 per unit
Table requirements 1 2 1 $30 per unit
Bookcase requirements 3 1 1 $25 per unit
Let the number of chairs = x
Let the number of tables = y
Let the number of bookcases = z
Objective function: maximize 20x + 30y + 25z
Subject to the constraints:
1x + 1y + 3z ≤ 600 (cutting operation)
1x + 2y + 1z <= 500 (assembly operation)
1x + 1y + 1z ≤ 300 (finishing operation)
Additionally, x, y, and z need to be non-negative (x >= 0, y >= 0, z >= 0).
Using a linear programming solver, we can input the objective function and constraints to find the optimal values for x, y, and z.
The optimal values are:
x = 200 (number of chairs)
y = 150 (number of tables)
z = 50 (number of bookcases)
Thus, the factory should manufacture 200 chairs, 150 tables, and 50 bookcases to maximize the profit.