Implementing inequality constrains in a non-liner optimisation

[jaganprabhu]

Homework Statement

Basically i have a minimize a least square function, and my function depends on three variables a,b,c and constraints a>=0, b>=c>=0 . I assigned initial values, minimum and maximum boundary limits for a,b &c.

Homework Equations

I have a problem in executing the constrain b>=c, what to do when this condition is violated?

The Attempt at a Solution

i tried like,
1) passing the initial values back to 'b' and 'c'
2) passing back my outer limit to 'b' and 'c'

Unfortunately i am not successfully by doing the above methods.

how to proceed further i do not know.

please help me

 

[nilesh_pat]

out. You could try setting the value of b to be equal to c if the constraint is violated. This will ensure that the constraint is always met, and will also make sure that the function is minimized.

 

[Mene]

I understand the importance of implementing constraints in optimization problems. In this case, the inequality constraints of a>=0, b>=c>=0 are important for ensuring the validity and accuracy of the results. When these constraints are violated, it can lead to inaccurate or even invalid solutions.

There are a few approaches you can take to address this issue. One option is to use a penalty function method, where a penalty term is added to the objective function to penalize violations of the constraints. This can help guide the optimization towards feasible solutions.

Another approach is to use a barrier function method, where a barrier function is added to the objective function to restrict the search space to feasible solutions. This can be particularly useful for nonlinear optimization problems.

Ultimately, the best approach will depend on the specific problem and constraints at hand. It may be helpful to consult with a colleague or seek out additional resources for guidance on how to handle these types of constraints in your optimization problem.