How do I pass additional parameters to the constraint and objective functions in the Optimization Toolbox functions?

I would like to parameterize my objective function and constraint function in my optimization problem using the Optimization toolbox. Typically this is needed when I want to use parameters and design variables together in an optimization problem.

Answer 1

[MathWorks Support Team]

You can pass additional parameters to the nonlinear constraint function as well as objective function using anonymous functions, inline functions, or function files for the objective and constraint functions. An example of this is given below.

Anonymous functions allow you to parameterize your objective and constraint functions.

The objective function "fun" can be defined in a function file:

function f = fun(x,p1)

f =  -x(1) * x(2) * x(3)*p1;

The nonlinear constraint function "nonlcon" is :

function [c, ceq] = nonlcon(x,p1,p2)

% Define two inequality constraints which use parameters P1 and P2

c(1) = x(1)*p1  + 2*x(2)*x(1)*p2 + 2*x(3) - p2;

c(2) = x(1)*x(2)-100;

% Define the equality constraints

ceq(1) = x(2) -x(1)*x(2);

ceq(2) = x(2) - x(1)*x(3);

The call to FMINCON where the additional parameter P1 is passed to the objective function, and parameters P1 and P2 to the constraint function is:

x0 = [10; 10; 10];

p1 = 1;

p2 = 72;

lb = [0 0 0];

ub = [ 50 50 50];

options = optimset('Largescale','off','Display','iter');

[x, fval] = fmincon(@(x)fun(x,p1), x0, [], [], [], [], lb, ub, @(x)nonlcon(x,p1,p2), options)

For simple objective functions, it is possible to define the objective function in the call to FMINCON, and have no objective function file:

[x, fval] = fmincon(@(x)-x(1)*x(2)*x(3)*p1, x0, [], [], [], [], lb, ub, @(x)nonlcon(x,p1,p2), options)

The ODE functions use the same convention for handling additional parameters as is described here. Additional information about the ODE solvers can be found in the related solution below.

[Triveni]

If i have to optimize matrix?

How can i optimize permutation?

A = [30 30 30 30 30 30 0 0 0 0 0 0 0 0 30 30 30 30 30 30 30 30]

My objective function is effective by different permutation of A.

i want minimum value of objective function F.

please write procedure for this too.

[Walter Roberson]

We are still waiting for a response from you in https://www.mathworks.com/matlabcentral/answers/260971-how-can-i-bound-initial-guess-during-optimization