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A solution to the subset sum problem using a branch-and-bound approach.
"""
Problem:
Given a vector of ints/floats V, find the number of length 3 subsets which have a sum < X.
Assume that V contains no duplicates.
"""
def num_subsets(V, X, N):
global count
count = 0
def branch_bound(V, X, N, i=0, s=0, t=0):
"""
Recursive branch-and-bound algorithm for the subset problem.
V, X, N: inputs based on the problem (N is max subset size)
i: current item index in V
s: current sum
t: number of items taken from V
Result is located in count variable defined above.
"""
# Number of items taken is N -> valid subset found
# Update overall count and return
if t == N:
global count
count += 1
return
# Depth limit for search; abort
elif i == len(V):
return
else:
# Take the current item *only* if it meets the constraint
if s + V[i] < X:
branch_bound(V, X, N, i+1, s+V[i], t+1)
# Always try *not taking* the current item
branch_bound(V, X, N, i+1, s, t)
# Run branch-and-bound
branch_bound(V, X, N)
# Return the number of valid subsets found
return count
if __name__ == '__main__':
# Sample with answer = 6
# Valid subsets: [1,2,3], [1,2,4], [1,2,5], [1,3,4], [1,3,5], [2,3,4]
V = [1, 2, 3, 4, 5]
X = 10
print('Valid subsets: {0}'.format(num_subsets(V, X, 3)))
# Larger problem with negative numbers and unsorted
# Max subset size is 10
V = [-10, 5, 4, 52, 77, 134, 22, 100, -59, 2, 16, 81, 3, 8, 21]
X = 150
print('Valid subsets: {0}'.format(num_subsets(V, X, 10)))
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