Optimization problem using gamultiobj

The goal is to find the pareto front of a problem using the following equations and constraints:

Equation 1:

Equation 2: (calulates the magnitude of C, D, and E once they are scaled by vector X)

F = sqrt( abs(C(:,1)*X(1) - C(:,2)*X(1)*X(2) + C(:,3)*X(3) + C(:,4)*X(3)*X(4)) ^ 2 +...

abs (D(:,1)*X(1) - D(:,2)*X(1)*X(2) + D(:,3)*X(3) + D(:,4)*X(3)*X(4)) ^ 2 +...

abs (E(:,1)*X(1) - E(:,2)*X(1)*X(2) + E(:,3)*X(3) + E(:,4)*X(3)*X(4)) ^ 2 )

where A3, A13, A23, Q, A34 are constant scalars, j is a complex number, and vectors C, D, and E are complex column vectors (e.g. C(:,1) has the size 100 * 1)

The constraints:

X(1) <= A constant value (JJ)

X(2) <= 1

X(3) <= A constant value (JJ)

X(4) <= 1

S >= some value

max(F) <= another value

Is this possible to be implemented using gamultiobj function?

[Alan Weiss]

I am not sure what your objectives are. And I am not sure if all of your objectives are real-valued. If you have real-valued objectives, then you can probably use gamultiobj, with a nonlinear constraint representing the lower bound on S and the upper bound on F.

Good luck,

Alan Weiss

MATLAB mathematical toolbox documentation