Does an additional parameter to a objective function always guarantee the better or equal optimization result?

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As the title, this seems to be intuitively correct. So, I am looking for some relevant theorem on this. In other words, 'Higher parameter space in some optimization problem gives the more optimal value than the original parameter space.

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If it's an additional parameter, then the new problem embeds the other one, which guarantees that the optimum cannot is at least as good. Of course, adding a parameter does not guarantee that the optimum will be (strictly) better.