Description:
binoptimize 0.0.10
bin_optimize
This project is an extension to binpacking problem. The utility provides
ability to optimize existing bins which are already allocated using any
bin_packing algorithm into n-1 bins.
The items in the bins are presented as a tuple of an identifier and
volume of the item.
Usage:
>>> from bin_optimize import optimize
>>> bins = {'b1': [('a1', 6), ('a5', 4.5), ('a9', 4)],
'b2': [('a2', 4), ('a6', 5), ('a10', 2)],
'b3': [('a3', 7), ('a7', 2), ('a11', 3)],
'b4': [('a4', 2), ('a8', 2), ('a12', 2), ('a13', 2), ('a15', 4)]}
>>> bin_to_reduce = 'b4'
>>> optimize(bins, bin_to_reduce)
{'b1': [('a1', 6), ('a5', 4.5), ('a9', 4), ('a8', 2)],
'b2': [('a2', 4), ('a6', 5), ('a10', 2), ('a12', 2), ('a15', 4)],
'b3': [('a3', 7), ('a7', 2), ('a11', 3), ('a13', 2), ('a4', 2)]}
The input bins can also have an empty bin.
>>> from bin_optimize import optimize
>>> bins = {'b1': [('a1', 6), ('a5', 4.5), ('a9', 4)],
'b2': [('a2', 4), ('a6', 5), ('a10', 2)],
'b3': [],
'b4': [('a4', 2), ('a8', 2), ('a12', 2), ('a13', 2), ('a15', 4)]}
>>> bin_to_reduce = 'b4'
>>> optimize(bins, bin_to_reduce)
{'b1': [('a1', 6), ('a5', 4.5), ('a9', 4)],
'b2': [('a2', 4), ('a6', 5), ('a10', 2)],
'b3': [('a12', 2), ('a13', 2), ('a15', 4), ('a4', 2), ('a8', 2)]}
License
For personal and professional use. You cannot resell or redistribute these repositories in their original state.
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