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Constrained optimization with objective function and constraints using different set of parameters

I am working on this constrained optimization problem. The objective function is the efficiency of the machine which is determined by 6 controllable variables. The constraint is the pressure can't exceed 10 psi. The pressure is dependent on a set of unknown parameters which most likely has little overlap with the 6 controllable variables.

In a nutshell

Objective function f(X) 
Constraints g(Y) < 10

Typical optimization problem usually has the same parameters for objective function and constraint. What should I do if objective and constaints are using different sets of variables?

Tags: optimization

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Replies to This Discussion

If it is truly the case that your objective function depends on a vector X, and your constraints depend on a vector Y, and there is no relationship between values of Y and values of X, then the constraints are irrelevant, and your problem is an unconstrained optimization problem.

My guess is that there is a relationship, and you just have to write out the math to know what that relationship is.

   -Irv Lustig
   Optimization Principal
   Princeton Consultants

If you dont know about the relationship between variables and responses, try using a designed experiment. If you have 6 parameters to test, you could use a definitive screening design. Use PSI and your other response in your model, then do a multi-objective function optimization. 



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