python - Calculate cost to combine subsets to get original set -
I have a list of items
[1,2,3]
And I have some subsets of the list above with a special cost such as
{(1): 5.0, (2): 3.0, (3): 2.5, (1,3): 6.0, (2,3): 5.0,}
I have to find a way to get the list above with the lowest price. For example, I could get [1,2,3] by combination (1), (2), (3) at the cost of 10.5,
combinations (1,3) and ( 2) with the cost of 9.0
and combination (1) and (2,3) 10.0 with the cost
. With my second choice I will be able to reach the lowest price.
because I consider that the solution I present combination of a set division of the above list [1,2,3] and if any special subtitles in Arabic, but this solution is not optimal their The set of lists is a huge cost associated with generating partitions.
set partitioning algorithm
Try:
- Cost of each object => Exclude any set of two objects with the value of each item.
- Three words whose cost is> = the cost of some combination of size set> 3.
- ...
greedy algorithms bit:
- One of the sets that are randomly given the rest of the larger size select
- once again it is left connects the largest set both
- covering
- < Em> and then , at least cost.
Above should give something better than a purely random selection.
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