I would like to know if any of you know whether there is a direct link between the computational effort of a multi-objective problem depending on whether the objective functions are heterogeneous or not. For example, 1) one objective is cost and a second objective is some kind of security index with a range [0, 1], 2) one objective is cost and we convert the second objective also to some kind of a security related cost (or we can try to convert the first objective to some normalized cost in a way that both objective functions have some homogeniety). Is there any research evidence whether such strategies can improve the computational time?
Sub question: Is there a difference when it comes to heuristic and non-heuristic algorithms in this regards?
Thank you!
Of course, there is a marked difference between the one-objective, two-objective, and three-objective problems, and so on, in general. And then, there is an additional complication associated with how heterogeneous the objectives are. To cut it short - it's a mess. :-)
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