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Answer :
Linear programming is a mathematical optimization technique used to maximize or minimize a linear objective function, subject to a set of linear constraints. It involves formulating a problem in a specific mathematical format that can be solved using linear programming algorithms.
To formulate the problem in linear programming format, we need to define the decision variables, objective function, and constraints.
Decision Variables:
Let:
- x be the number of bedroom sets to be ordered.
- y be the number of living room sets to be ordered.
Objective Function:
The objective is to maximize the total revenue. Since the bedroom sets produce revenue of $1000 each and the living room sets produce revenue of $500 each, the objective function can be defined as follows:
Maximize: Revenue = 1000x + 500y
Constraints:
1. Showroom Space Constraint: The total showroom space of 40,000 square feet should be completely filled with these sets, taking into account the average space occupied by each set:
400x + 500y ≤ 40,000
2. Time Constraint: The available time for unloading is 980 minutes. The time required to unload a bedroom set is 14 minutes, and the time required to unload a living room set is 7 minutes:
14x + 7y ≤ 980
3. Minimum Order Constraint: A minimum of 20 living room sets should be ordered:
y ≥ 20
4. Non-negativity Constraint: The number of sets ordered cannot be negative:
x, y ≥ 0
Now, let's determine the optimal solution by solving this linear programming problem.
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