Hmm, yes but how can we use information from the pareto optimal front to make a decision? In what way does it provide more information to our problem than if we just picked our coefficients at the beginning and performed single objective optimization? Can you provide a few examples?
@@paretos-com Thank you very much for the link! In the paper it is written "The DTLZ suite of benchmark problems, created by Deb et al., is unlike the majority of multiobjective test problems in that the problems are scalable to any number of objectives." Is there a particular reason to limit the number of objectives to 10? In my own experiments I was assuming that I could set m from 3 up to 60 objectives (for extreme stress tests).
Nice video ! i have an academic project on data assimilation and optimisation problems, can you give us more videos on how to minimise functions? and how to move from data assimilations to experimental measurements ( observations ) and vice versa ? I will be very thankful !!
