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valentinak56 [21]
2 years ago
12

Find the maximum of the objective function, f, subject to the constraints f = 4x + 3y

Mathematics
1 answer:
Scilla [17]2 years ago
7 0

Maximum value = 880/3.

Maximizing the objective function in the LP model means that the value occurs in an acceptable set of decisions. Linear programming refers to selecting the best alternative from the available alternatives that can represent the objective and constraint functions as linear mathematical functions.

As mentioned above, the equation is an example of a constraint. You can use this to think about what it means to solve equations and inequalities. For example, solving 3x + 4 = 10 yields x = 2. This is an easy way to express the same constraints.

Learn more about constraints here: brainly.com/question/8729359

#SPJ4

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Please help this is due tomorrow morning
Minchanka [31]

Answer:

I can try to help you..uhh alright 1ll it's definitely multiplying by 4 on the bottom but adding 1 one the top. I'm not sure if i'll be correct but try 1 and 4 i'm so sorry if it doesn't help!

7 0
3 years ago
The product of 9 and sum of a number x and 12
mr_godi [17]

Answer:

9(x + 19)

Step-by-step explanation:

Product is a multiplication key word where you'll usually always put parenthesis when multiplying, and where the keyword sum comes you'd add x and 12 for your equation :)

5 0
3 years ago
The least squares regression line minimizes the sum of the:
lorasvet [3.4K]

Answer:

d) Squared differences between actual and predicted Y values.

Step-by-step explanation:

Regression is called "least squares" regression line. The line takes the form = a + b*X where a and b are both constants. Value of Y and X is specific value of independent variable.Such formula could be used to generate values of given value X.

For example,

suppose a = 10 and b = 7. If X is 10, then  predicted value for Y of 45 (from 10 + 5*7). It turns out that with any two variables X and Y. In other words, there exists one formula that will produce the best, or most accurate predictions for Y given X. Any other equation would not fit as well and would predict Y with more error. That equation is called the least squares regression equation.

It minimize the squared difference between actual and predicted value.

3 0
3 years ago
My question is what is 8.7+5.4​
alex41 [277]
The awnser to this question is 14.1
5 0
3 years ago
Read 2 more answers
¿Cómo las razones de seno y cos<br>eno son semejantes?​
Sauron [17]
Las razones de los lados de un triángulo rectángulo se llaman razones trigonométricas.

Espero te ayude :)
6 0
3 years ago
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