A toy factory manufactures three kinds of toys: cars, motorcycles, and boats. One toy car makes $20 profit, one toy motorcycle makes $15 profit, and one toy boat makes $25 profit. There are three departments of labour: casting, which has 8 workers; assembly, which has 12 workers; quality control, which has 10 workers.
Every day, the labour is allocated as follows: a toy car requires 2 casting, 2 assembly, 2 quality control; a toy motorcycles requires 1 casting, 2 assembly, 1 quality control; a toy boat requires 2 casting, 3 assembly, 3 quality control.
What is the maximum profit per day (in dollars) the toy company can achieve?
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but you have failed to show that there is only 1 solution giving a profit of 100. In fact, there is another solution namely 2 cars, 4 motorcycles, and 0 boats.
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You're right. Editing solution.
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Does this solution not give more slack using the constraints you've given ? If so it wouldn't be optimal ?
I don't understand why did you select the
c
variable to enter the basis first. I thought that simplex requires us to select the variable with the largest coefficient to enter the base, i.e.
b
should enter as it has a coefficient of 25, which is bigger than 20 = the coefficient of
c
Let
a = the number of toy cars produced
b = the number of toy motorcycles produced
c = the number of toy boats produces
To maximize the profit, we should use all the workers : casting, which has 8 workers; assembly, which has 1 2 workers; quality control, which has 1 0 workers.
For casting, which has 8 workers, we have
2 a + b + 2 c = 8 … … … … ( 1 )
For assembly, which has 1 2 workers, we have
2 a + 2 b + 3 c = 1 2 … … … … ( 2 )
For quality control, which has 1 0 workers, we have
2 a + b + 3 c = 1 0 … … … … ( 3 )
Solve for a , b and c
( 3 ) − ( 1 ) we have
c = 2
( 2 ) − ( 3 ) we have
b = 2
For b = 2 and c = 2 we have
a = 1
The number of toy motorcycles produced to maximize the profit = 2
This solution shows that a solution exists in which 2 motorcycles are produced and each labor resource is used fully. However, this does not prove that the solution maximizes profit. Your solution does happen to maximize profit, but imagine how the answer would be different if there was $50 profit per boat.
You need to use linear programming to ensure that you have the optimal solution, as my solution shows.
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Let c be the number of cars produced, let m be the number of motorcycles produced, and let b be the number of boats produced. The goal is to maximize the objective function:
f ( c , m , b ) = 2 0 c + 1 5 m + 2 5 b
Subject to the constraints:
⎩ ⎪ ⎪ ⎪ ⎪ ⎨ ⎪ ⎪ ⎪ ⎪ ⎧ 2 c + m + 2 b 2 c + 2 m + 3 b 2 c + m + 3 b c , m , b ≤ 8 ≤ 1 2 ≤ 1 0 ≥ 0 Casting Assembly Quality Control
Following the simplex algorithm , convert to a system of equations:
⎩ ⎪ ⎪ ⎨ ⎪ ⎪ ⎧ z − 2 0 c 2 c 2 c 2 c − + + + 1 5 m m 2 m m − + + + 2 5 b 2 b 3 b 3 b + s 1 + s 2 + s 3 = = = = 0 8 1 2 1 0 ( 0 ) ( 1 ) ( 2 ) ( 3 )
In augmented matrix form:
⎣ ⎢ ⎢ ⎡ 1 0 0 0 − 2 0 2 2 2 − 1 5 1 2 1 − 2 5 2 3 3 0 1 0 0 0 0 1 0 0 0 0 1 0 8 1 2 1 0 ⎦ ⎥ ⎥ ⎤ ( 0 ) ( 1 ) ( 2 ) ( 3 )
The current basic solution, ( z , c , m , b , s 1 , s 2 , s 3 ) , is ( 0 , 0 , 0 , 0 , 8 , 1 2 , 1 0 ) . It is not optimal because there are negative coefficients in row ( 0 ) .
Enter c as a basic variable. Observe the ratios for each row:
( 1 ) : ( 2 ) : ( 3 ) : 2 8 = 4 2 1 2 = 6 2 1 0 = 5
The minimum ratio is in row ( 1 ) . Eliminate c in all rows except row ( 1 ) :
⎣ ⎢ ⎢ ⎡ 1 0 0 0 0 2 0 0 − 5 1 1 0 − 5 2 1 1 1 0 1 − 1 − 1 0 0 1 0 0 0 0 1 8 0 8 4 2 ⎦ ⎥ ⎥ ⎤ ( 0 ) ( 1 ) ( 2 ) ( 3 )
The current basic solution is ( 8 0 , 4 , 0 , 0 , 0 , 4 , 2 ) . It is not optimal because there are negative coefficients in row ( 0 ) .
Enter m as a variable. Observe the ratios for each row:
( 1 ) : ( 2 ) : 1 8 = 8 1 4 = 4
The minimum ratio is in row ( 2 ) . Eliminate m in all rows except row ( 2 ) :
⎣ ⎢ ⎢ ⎡ 1 0 0 0 0 2 0 0 0 0 1 0 0 1 1 1 5 2 − 1 − 1 5 − 1 1 0 0 0 0 1 1 0 0 4 4 2 ⎦ ⎥ ⎥ ⎤ ( 0 ) ( 1 ) ( 2 ) ( 3 )
Note that if this solution is feasible, then it is optimal, because all coefficients in row ( 0 ) are positive. Eliminate b in all rows except ( 3 ) to find the solution:
⎣ ⎢ ⎢ ⎡ 1 0 0 0 0 2 0 0 0 0 1 0 0 0 0 1 5 3 0 − 1 5 − 1 1 0 0 − 1 − 1 1 1 0 0 2 2 2 ⎦ ⎥ ⎥ ⎤ ( 0 ) ( 1 ) ( 2 ) ( 3 )
This gives the solution ( 1 0 0 , 1 , 2 , 2 , 0 , 0 , 0 ) . Thus, the factory's maximum profit is $ 1 0 0 .
Edit : There is more than one optimal solution. There exists an edge of the feasible region (the intersection of the 1st and 2nd equations) that is parallel to the objective function. Therefore, every point on that edge is also an optimal solution. An integer solution is ( 1 0 0 , 2 , 4 , 0 , 0 , 0 , 0 ) (2 cars, 4 motorcycles, 0 boats). Note that the maximum profit is the same.