Constraints of an L-shaped feasible region

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Also, you have a typo in the definition of Ry. The first inequality should have y as the left side and the second inequality should have x as the left side.
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Jimbrisky
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I am writing the constraints for the feasible region within the L-shaped feasible region. The diagram is at this http://www.mathworks.com/help/optim/ug/writing-constraints.html

Are these equations the right constraints:

–1 ≤ x ≤ 1 and 0 ≤ y ≤ 1

Thanks for the help.
 
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  • #2
Jimbrisky said:
I am writing the constraints for the feasible region within the L-shaped feasible region. The diagram is at this http://www.mathworks.com/help/optim/ug/writing-constraints.html

Are these equations the right constraints:

–1 ≤ x ≤ 1 and 0 ≤ y ≤ 1
No. These inequalities give you the rectangle whose corners are at (-1, 1), (1, 1), (1, 0), and (-1, 0). To get the whole L-shaped region you also need these constraints: 0 ≤ x ≤ 1 and -1 ≤ y ≤ 0.

The diagram at the page you linked to says this (slightly changed to use your x, y notation):

A point is in the rectangle –1 ≤ x ≤ 1 and 0 ≤ y ≤ 1 OR a point is in the rectangle 0 ≤ x ≤ 1 and -1 ≤ y ≤ 0
 
  • #3
@Mark44, based on your explanation can I write the constraints for the feasible region as the union of two sets, Rx∪Ry, where

Rx:={(x,y):−1≤x≤1,0≤y≤1}

Ry:={(x,y):0≤x≤1,−1≤y≤1}.

Thanks for the help.
 
  • #4
Yes, although I don't know why you call one set Rx and the other one Ry. Better names might be R1 and R2.
 
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I would like to clarify that the constraints provided are not sufficient to define the L-shaped feasible region. The constraints should also consider the intersection point of the two lines in the L-shape, as well as any other relevant boundaries or conditions that may affect the feasibility of the region. Additionally, the constraints should be written in a way that clearly defines the boundaries of the region and allows for proper optimization and analysis. It is important to carefully consider all factors and variables when defining constraints in order to accurately represent the L-shaped feasible region.
 

FAQ: Constraints of an L-shaped feasible region

What is an L-shaped feasible region?

An L-shaped feasible region is a two-dimensional space that represents the set of all possible solutions to a linear programming problem. It is characterized by a distinct L-shape, with one side representing the constraints and the other side representing the objective function.

What are the constraints of an L-shaped feasible region?

The constraints of an L-shaped feasible region are linear inequalities that limit the possible solutions to the problem. These constraints can be represented by lines on the graph of the feasible region, and the intersection of these lines creates the L-shape.

How are the constraints of an L-shaped feasible region determined?

The constraints of an L-shaped feasible region are determined by the given problem and its specific requirements. These constraints are usually based on resource limitations, such as time, space, or budget, and must be represented in the form of linear inequalities.

What is the significance of the L-shaped feasible region?

The L-shaped feasible region is significant because it allows us to visualize and understand the potential solutions to a linear programming problem. By graphing the constraints and objective function, we can easily identify the optimal solution and any potential trade-offs between different variables.

Can an L-shaped feasible region have more than one optimal solution?

Yes, an L-shaped feasible region can have more than one optimal solution, depending on the problem and its constraints. In some cases, the optimal solution may occur at a vertex of the L-shaped region, while in others, it may occur along one of the edges. This is why it is important to carefully analyze the problem and its constraints to determine the most appropriate and feasible solution.

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