Given the objective function which is to minimize C=50x+30y and the vertices in the choices are the extreme points in the feasible region of the constraints, what is the optimum solution of the linear model?
but I don't know
Oh, the optimum solution? Well, that's where all our linear dreams come true! To find it, we need to consider the extreme points of the feasible region.
But before we start, let me just say that finding the optimum solution is like finding the perfect punchline – it takes a bit of work, but it's totally worth it!
Now, let's focus on those extreme points. We need to evaluate the objective function C=50x+30y for each vertex. Just like a clown juggling, we'll crunch those numbers!
Once we've computed the objective function for each vertex, we'll simply choose the one that gives us the minimum value. It's like finding the smallest custard pie in a pie fight!
And there you have it, my friend – the optimum solution! Just remember to wear a smile while you're at it.
To find the optimum solution of a linear model with the given objective function and vertices, we need to evaluate the objective function at each vertex and determine the vertex with the lowest value.
The objective function is C = 50x + 30y.
Evaluate the objective function at each vertex:
1. Evaluate C for the first vertex:
Let's say the first vertex is (x1, y1).
C1 = 50(x1) + 30(y1)
2. Evaluate C for the second vertex:
Let's say the second vertex is (x2, y2).
C2 = 50(x2) + 30(y2)
3. Evaluate C for the third vertex:
Let's say the third vertex is (x3, y3).
C3 = 50(x3) + 30(y3)
4. Evaluate C for the fourth vertex:
Let's say the fourth vertex is (x4, y4).
C4 = 50(x4) + 30(y4)
Compare the values of C at each vertex and choose the vertex with the lowest value as the optimum solution.
To determine the optimum solution of the linear model, you need to evaluate the objective function at each vertex (extreme point) and find the one that yields the minimum value of the objective function.
Here are the steps to find the optimum solution:
1. Identify the vertices of the feasible region. These vertices are the extreme points where the constraints intersect.
2. Evaluate the objective function C=50x+30y at each vertex. Substitute the x and y values of each vertex into the objective function to calculate the corresponding objective function value.
3. Compare the objective function values obtained from Step 2 and find the minimum value. This vertex will correspond to the optimum solution of the linear model.
By following these steps, you will be able to determine the optimum solution for the given linear model.