algorithmic modeling for Rhino
I would like to aks your help, I'd like to make a grasshopper program which helps to solve my problem, i don't know python/C#/VB coding that's why I ask your help.
The problem is the following (It's a bit similar to the Knapsack problem):
I have a Variable --> X
I Have fix numbers (can we call "pieces") 9,12,15,18
I'd like to reach the X, with the summing of these numbers and using the minimum pieces ,it can't be lower than X, but it can be higher, maximum with 3.
After this it has to found the most optimal combination which mostly use the same pieces
The wrong solution is like = 1pcs of 18
= 9pcs of 9
Sum of pieces are 10
= 3pcs of 18
= 1pcs of 15
= 1pcs of 12
= 2pcs of 9
Sum of pieces are 7
The right solution in this case = 5pcs of 18
= 1pcs of 9
(5*18)+(1*9)=99 it's good beacuse it's over with maximum 3 and uses the minimum pieces
Then it sends to a list like
18 : 5pcs
15 : 0pcs
12 : 0pcs
9 : 1pcs
Can somebody help me ? Or is it possible to make this ?
One method that springs to mind would be combinatorial generation. That is, for a list of values, generate all combinations/permutations of these. There's a thread on various options in GH here (I'd personally recommend the Python itertools one). So in your case, for instance: generate all combinations (using the second argument to generate only sets of three), calculate the sum of all the generated sets, and then find the sum closest to X.
Here's an quick go (didn't test, so might be buggy, looks okay though):
Edit: You might expand this to start the search with the SetSize at 1, check if this generates a result that is within some tolerance distance from X, if not, jump to 2, if not, jump to 3 etc. A less exhaustive/brute force method might be to implement Galapagos for the search, but with smaller sets I suspect that won't be an advantage (also, it comes with its own can of worms). That said, the search space and amount of possible combinations grows rapidly with these cases.
I used your python script and I'm getting closer to the solution,
Here is where i'm standing now.
I set 79 as goal, my result is 81 which is good, but not the best optimalization,
Becuase it gives me 3pcs of 12 and 5 pcs of 9
the good solution would be 4pcs of 18 and 1pcs of 9
In that case, you might have more succes using the function combinations_with_replacement():
Edit: Also note that the script is written assuming floats, you might need to edit it for integer logics (i.e. floor/ceiling type pitfalls etc.).
i don't understand pyhton unfortunately, where can i edit floats to integer?
In the GHPython component script editor (double-click one and it opens up, like in the screenshots).
There's a Logarithm component. I don't think I understand the question though, perhaps better if you create a new topic.
exactly my question isn't clear enough,
i will formulate differently.
i am sorry to stay on for this
i tried the expression editor
i have the 1519 invalid expression error message
Hey, I ran into the same error and found a solution.
So for anyone who still has this issue:
Use: Log(x,(CDbl(y))) instead of Log(x[,y])
for "x,y" input
(works also for other formats than sliders as inputs;)
A bit lost as well, there are a couple of logarithmic functions in the Python math module as well (if that was the question).
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