[mccourt]

You make a perfectly accurate point that, in practice, it is unlikely one would be able to make such a prediction without significant info about the model. The above comment was meant in more of a post hoc "we've executed our multicriteria optimization, approximated our Pareto frontier, now let's make a decision" sense, not within a specific scalarization context. Indeed sensitivity analysis on the gamma parameter is very important; I tried to hint at that by showing that the interplay of the choice of currency and the gamma on the optimal value is nontrivial (though predictable since this is just a toy problem).

Do you happen to have any references talking about such sensitivity analysis on scalarization parameters? I would love to add them to my reading list. Thanks.

[sevensor]

I don't have any references -- I'm going off something one of my committee members said. But the basic idea is just that, if your weight is 0.2, you want to make sure you also obtain solutions for 0.18 and 0.22, to give you some sense of whether you're on the edge of a cliff. This is pretty cheap in general for convex optimization problems because you've already got a solution that should be close to optimal for the new weight.

[mccourt]

Good call - if the problem is well behaved then small changes in gamma should be able to use the previous solution as an initial guess. And I absolutely agree with the robustness idea you're talking about; I was hinting at it when I was talking about the impact of choice of currency. For a well scaled problem there is a consistent and well-behaved impact on the solution for small changes in gamma. But when the currency was changed to RMB, small changes in gamma no longer had a consistent impact on the optimum.