Linear programming: simplex question (might belong in precal)

In summary, the question asks for the optimal number of sets to be produced in order to maximize profit for the Cut-Right Company. Using the Simplex algorithm, the optimal solution is 200 deluxe sets and 100 basic sets, resulting in a maximum profit of $8,000. Remember to update the cost coefficient "a" after performing pivot operations to ensure correct calculations.
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Homework Statement



Original question: The Cut-Right Company sells sets of kitchen knives. The Basic Set consists of 2 utility knives and 1 chef’s knife. The Regular Set consists of 2 utility knives, 1 chef’s knife, and 1 slicer. The Deluxe Set consists of 3 utility knives, 1 chef’s knife, and 1 slicer. Their profit is $30 on a Basic Set, $40 on a Regular Set, and $60 on a Deluxe Set. The factory has on hand 800 utility knives, 400 chef’s knives, and 200 slicers. Assuming that all sets will be sold, how may of each type should be produced in order to maximize profit? What is the maximum profit?

Homework Equations



s1, s2, s3 are slack variables
x1, x2, x3 are all non-negative

x1 = # of basic sets produced
x2 = # of regular sets produced
x3 = # of deluxe sets produced

2*x1 + 2*x2 + 3*x3 + s1 = 800
x1 + x2 + x3 + s2 = 400
x2 + x3 + s3 = 200

a is the profit function given by:
a = 30*x1 + 40*x2 + 60*x3

The Attempt at a Solution



pivot.jpg


I circled the pivot element in row3,col3. It's a "1".

I know I chose the pivot correctly(chose the most negative number in the bottom row, then found the column entry that is least when divided into the right-most column). Then I perform row operations to get all the rest of the numbers in the pivot column to be 0. Then I perform a row operation to turn the entry in the last row of the pivot column to 0. This makes the entire last row positive so the simplex algorithm is supposedly done--but it's not. The correct answer requires 200 deluxe sets and 100 basic sets be produced.

I notice that I still have slack variables as basic variables. My guess is that I either performed the row operations incorrectly or there is some other step that I am overlooking. Ideas?
 
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  • #2
Hi,

Hopefully, I am not late to help.

After performing the row (pivot) operations, remember to update the "a", your cost coefficient of the entering variable x3 into the 3rd row, i.e. now "a" for the 3rd row is updated from 0 to 60!
I think this is what causes the error in your Simplex calculations.
Redo your workings again, and I am sure you can get the correct optimal solution!

If you still can't find it, you can pm me here.
 
Last edited:

1. What is linear programming?

Linear programming is a mathematical technique used to optimize a linear objective function, subject to a set of linear constraints. It is commonly used in business and economics to maximize profits or minimize costs.

2. What is the simplex method?

The simplex method is a popular algorithm used to solve linear programming problems. It involves creating a series of linear equations and iteratively finding the optimal solution by moving along the edges of a geometric shape called a simplex.

3. What are the key components of a linear programming problem?

A linear programming problem consists of an objective function, decision variables, and constraints. The objective function defines the quantity to be optimized, while the decision variables represent the unknown quantities. The constraints limit the values that the decision variables can take on.

4. How is the optimal solution found in linear programming?

The optimal solution in linear programming is found by using the simplex method. This involves creating a feasible solution, then improving it until the optimal solution is reached. The solution is reached when all constraints are satisfied and no further improvement is possible.

5. What are some real-world applications of linear programming?

Linear programming is used in a variety of industries, such as manufacturing, transportation, and finance. It can be used to determine the most cost-effective way to produce goods, optimize transportation routes, and allocate resources. It is also used in decision-making processes, such as portfolio optimization and project planning.

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