I was wondering if it’s possible to group numbers into a list so that each list would have a sum close to a number i specified?

for example, i have numbers:
1,3,5,6,7,9,12
and i want a sum of list to be as close to 12 as possible
so it’d split these number into lists like:
[0] 12
[1] 9, 3
[2] 7, 5
[3] 6,1

That’s a combinatorial problem (more specifically 1-D bin packing), and I don’t think there’s a simple way to to express it in a form that can be directly accepted by Galapagos.

It’s definitely possible though, and there are lots of heuristics for solving these problems - you can google them, but they would definitely involve some scripting.

''' Partition a list into sublists whose sums don't exceed a maximum
using a First Fit Decreasing algorithm. See
http://www.ams.org/new-in-math/cover/bins1.html
for a simple description of the method.
'''
class Bin(object):
''' Container for items that keeps a running sum '''
def __init__(self):
self.items = []
self.sum = 0
def append(self, item):
self.items.append(item)
self.sum += item
def __str__(self):
''' Printable representation '''
return 'Bin(sum=%d, items=%s)' % (self.sum, str(self.items))
def pack(values, maxValue):
values = sorted(values, reverse=True)
bins = []
for item in values:
# Try to fit item into a bin
for bin in bins:
if bin.sum + item <= maxValue:
#print 'Adding', item, 'to', bin
bin.append(item)
break
else:
# item didn't fit into any bin, start a new bin
#print 'Making new bin for', item
bin = Bin()
bin.append(item)
bins.append(bin)
return bins
from Grasshopper import DataTree
from Grasshopper.Kernel.Data import GH_Path
result = DataTree[float]()
for path, bin in enumerate(pack(values, maxValue)):
result.AddRange(bin.items, GH_Path(path))