Basic feasible solution, permuting the row

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In summary: Therefore, the number of possible combinations is 2^5 = 32. However, since we are looking for different dictionaries, we must subtract the two dictionaries already found in part b, leaving us with 30 different dictionaries.
  • #1
pinki82
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FOr the problem,
Max(-x_1 - 2x_2 + 3x_5)
x_1 + x_2 + 2x_3 + 3x_4 + x_5 <= 1
2x_1 - x_2 + 4x_3 + 6x_1 - x_5 <= 2
x_j >= 0, j= 1,...,5

A) show that x_1 = 1, x_2= x_3= x_4= x_5 = 0 is a basic feasible solution.
B) Find two different dictionaries..(i.e. Not obtained by permuting the rows) that have this point as a basic solution.
C) How many different dictionaries have this point as basic solution.

i am so lost.. especially in part b and c.
please help..any hint or help would be really appreciated!
thanks.
 
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  • #2
A) To show that x_1 = 1, x_2= x_3= x_4= x_5 = 0 is a basic feasible solution, we must first make sure that it satisfies all of the constraints. The given solution satisfies all of the constraints, as it meets each constraint's lower bound (zero), and does not exceed the upper bound. Therefore, this solution is a basic feasible solution.

B) Two different dictionaries that have this point as a basic solution are:

Dictionary 1:
x_1 = 1 (basic)
x_2 = 0 (non-basic)
x_3 = 0 (non-basic)
x_4 = 0 (non-basic)
x_5 = 0 (non-basic)

Dictionary 2:
x_1 = 0 (non-basic)
x_2 = 1 (basic)
x_3 = 0 (non-basic)
x_4 = 0 (non-basic)
x_5 = 0 (non-basic)

C) The number of different dictionaries that have this point as a basic solution is five, since there are five variables, each of which can be either basic or non-basic.
 

Related to Basic feasible solution, permuting the row

What is a basic feasible solution?

A basic feasible solution is a solution to a linear programming problem that satisfies all of the constraints and has all non-negative variables. It is considered a feasible solution because it falls within the feasible region, or the area defined by the constraints of the problem.

What is permuting the row in relation to basic feasible solutions?

Permuting the row refers to the process of rearranging the order of the rows in a linear programming problem. This can be done to simplify the problem or to find a better solution. In the context of basic feasible solutions, permuting the row can help identify the optimal solution by reordering the constraints in a way that makes it easier to find a feasible solution.

How do you determine if a basic feasible solution is optimal?

A basic feasible solution is considered optimal if it is the best possible solution for a linear programming problem. This means that it maximizes the objective function, or the goal of the problem, while still satisfying all of the constraints. To determine if a basic feasible solution is optimal, you can use the simplex method or other optimization techniques.

Can there be multiple basic feasible solutions for a linear programming problem?

Yes, there can be multiple basic feasible solutions for a linear programming problem. This is because the feasible region, or the area defined by the constraints, can have multiple points that satisfy all of the constraints. However, only one of these solutions will be optimal, meaning it maximizes the objective function.

What is the significance of finding a basic feasible solution?

Finding a basic feasible solution is significant because it allows us to identify the optimal solution to a linear programming problem. It also helps us understand the feasible region and how different constraints can affect the possible solutions. Additionally, finding a basic feasible solution can provide insights into the problem and help make decisions in real-world applications.

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