Optimising a multivariable-multiobjective function with known the best objective values
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I have a displacement error function with two coefficients as input ( coefficients are the parameters that need to be optimised), and the output of the function (cost function) is a vector including six numbers showing the error of the function with coefficient inputs.
[y1 y2 y3 y4 y5 y6 ]=cost (x1,x2)
The ideal coefficient is the coefficient that yields the cost function value of zero (it means that the best combination of x1 and x2 should give y1=y2=y3=y4=y5=y6=0); however,, assigning various coefficient (variables), the output may become positive or negative.
I am currently running to the problem that the optimisation loop is trying to minimise the cost function by tailoring to more negative values, which is wrong. It should try to push the cost function to a value of zero.
I cannot use absolute values since it is physically wrong, and the results won't be correct values.
Is there any way to assign the objective value of zero to the function and make Matlab push the cost function to zero?
I am currently using gamultiobj function.