I’m trying to implement functionality similar to Excel solver, but I’m not having much luck. I’ve looked at multiobjective optimization but the examples I’m seeing aren’t helping and I can’t seem to find much more than that. Here’s a hypothetical scenario:
I have a staff of 50 and I have to cut 25. Each employee has a salary and a “score”. I have to stay within a budget (total salary of the remaining 25) and want to maximize the team “score”.
It’s a pretty straightforward “excel solver” scenario. Is this possible with multiobjective optimization or some other Knime function?
Hi @holmes -
In theory this should be possible using a variation on this workflow that you’ve already found:
If you input a table with salary and score for each of your fifty staff, then use the Multiobjective Subset Selection (NSGA-II) with a subset of 25, then you could set objectives for total salary and max of team score. Then do the Multiobjective Score Computation to see what the results are for particular subsets.
I will confess that I haven’t used these nodes myself so there may be some nuance I’m missing. Do you have a dummy dataset we could try?
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