The answer depends on the feasible region and there is no information on which to determine that.
If you want to ask questions about the "region shown", then it would have helped if you could make sure that there is some region that is shown. However, given the limitations of the browser used by this site, you do not have much of a hope!
1y
Linear programming is just graphing a bunch of linear inequalities. Remember that when you graph inequalities, you need to shade the "good" region - pick a point that is not on the line, put it in the inequality, and the it the point makes the inequality true (like 0
An open or closed circle are used to graph an inequality in one variable. An open circle is used if the value at the end point is excluded from the feasible region while a closed circle is used if the value at that point is within the accepted region.
By taking the derivative of the function. At the maximum or minimum of a function, the derivative is zero, or doesn't exist. And end-point of the domain where the function is defined may also be a maximum or minimum.
Given definitions, or descriptions at least, of "point D" and "the feasible region",I might have had a shot at answering this one.
To find the maximum value of 2x + 5y within the feasible region, you would need to evaluate the objective function at each corner point of the feasible region. The corner points are the vertices of the feasible region where the constraints intersect. Calculate the value of 2x + 5y at each corner point and identify the point where it is maximized. This point will give you the maximum value of 2x + 5y within the feasible region.
If you want to ask questions about the "region shown", then it would have helped if you could make sure that there is some region that is shown. However, given the limitations of the browser used by this site, you do not have much of a hope!
Feasible regions have more corners when there are more constraints that intersect at a single point, creating a corner. If there are more constraints that intersect at different points, the feasible region will have more corners. In general, the number of corners in a feasible region is determined by the number of constraints and how they interact.
1y
1y
feasible region gives a solution but not necessarily optimal . All the values more/better than optimal will lie beyond the feasible .So, there is a good chance that the optimal value will be on a corner point
The question cannot be answered because:there is no symbol shown between 2y and x,there is no information on the feasible region.The question cannot be answered because:there is no symbol shown between 2y and x,there is no information on the feasible region.The question cannot be answered because:there is no symbol shown between 2y and x,there is no information on the feasible region.The question cannot be answered because:there is no symbol shown between 2y and x,there is no information on the feasible region.
It is usually the answer in linear programming. The objective of linear programming is to find the optimum solution (maximum or minimum) of an objective function under a number of linear constraints. The constraints should generate a feasible region: a region in which all the constraints are satisfied. The optimal feasible solution is a solution that lies in this region and also optimises the obective function.
Linear programming is just graphing a bunch of linear inequalities. Remember that when you graph inequalities, you need to shade the "good" region - pick a point that is not on the line, put it in the inequality, and the it the point makes the inequality true (like 0
To find the maximum value of 3x + 3y in the feasible region, you will need to determine the constraints on the variables x and y and then use those constraints to define the feasible region. You can then use linear programming techniques to find the maximum value of 3x + 3y within that feasible region. One common way to solve this problem is to use the simplex algorithm, which involves constructing a tableau and iteratively improving a feasible solution until an optimal solution is found. Alternatively, you can use graphical methods to find the maximum value of 3x + 3y by graphing the feasible region and the objective function 3x + 3y and finding the point where the objective function is maximized. It is also possible to use other optimization techniques, such as the gradient descent algorithm, to find the maximum value of 3x + 3y within the feasible region. Without more information about the constraints on x and y and the specific optimization technique you wish to use, it is not possible to provide a more specific solution to this problem.
An open or closed circle are used to graph an inequality in one variable. An open circle is used if the value at the end point is excluded from the feasible region while a closed circle is used if the value at that point is within the accepted region.