subset-sum

问题 I have a script below that gives the closest 2 values to a given sum. It also iterates through a list of given sums and after each iteration removes the numbers that have already been used. I need to modify this script so that it produces a necessary amount of values closest to each sum, rather than 2. The script needs to accept float values and cannot re-use values. Effectively it needs to pick the most efficient set closest to target, update the set to remove values used, then move on to

问题 I have a script below that gives the closest 2 values to a given sum. It also iterates through a list of given sums and after each iteration removes the numbers that have already been used. I need to modify this script so that it produces a necessary amount of values closest to each sum, rather than 2. The script needs to accept float values and cannot re-use values. Effectively it needs to pick the most efficient set closest to target, update the set to remove values used, then move on to

问题 Decription Given a set of numbers S. Find maximum sum such that Sum(A 1 ) = Sum(A 2 ) Where, A 1 ⊂S and A 2 ⊂S and A 1 ⋂A 2 =∅ And Sum(X), is the sum of all elements within the set X. Approach Brute Force The easiest approach is: print maximumSum(0,0,0) def maximumSum(index,sum1,sum2): ans=0 if sum1 == sum2: ans=sum1 if index >= len(S): return ans m1=maximumSum(index+1,sum1+S[index],sum2) m2=maximumSum(index+1,sum1,sum2+S[index]) m3=maximumSum(index+1,sum1,sum2) return max(m,m1,m2,m3) Time

问题 Decription Given a set of numbers S. Find maximum sum such that Sum(A 1 ) = Sum(A 2 ) Where, A 1 ⊂S and A 2 ⊂S and A 1 ⋂A 2 =∅ And Sum(X), is the sum of all elements within the set X. Approach Brute Force The easiest approach is: print maximumSum(0,0,0) def maximumSum(index,sum1,sum2): ans=0 if sum1 == sum2: ans=sum1 if index >= len(S): return ans m1=maximumSum(index+1,sum1+S[index],sum2) m2=maximumSum(index+1,sum1,sum2+S[index]) m3=maximumSum(index+1,sum1,sum2) return max(m,m1,m2,m3) Time

问题 Please note that this is required for a C# .NET 2.0 project ( Linq not allowed ). I know very similar questions have been asked here and I have already produce some working code (see below) but still would like an advice as to how to make the algorithm faster given k and s conditions. This is what I've learnt so far: Dynamic programming is the most efficient way to finding ONE (not all) subsets. Please correct me if I am wrong. And is there a way of repeatedly calling the DP code to produce

来源： https://stackoverflow.com/questions/34274701/subset-sum-find-all-subsets-that-add-up-to-a-number

来源： https://stackoverflow.com/questions/34274701/subset-sum-find-all-subsets-that-add-up-to-a-number

来源： https://stackoverflow.com/questions/34274701/subset-sum-find-all-subsets-that-add-up-to-a-number

问题 I will be happy to get some help. I have the following problem: I'm given a list of numbers seq and a target number and I need to write 2 things: A recursive solution that returns True if there is a sum of a subsequence that equals the target number and False otherwise. example: subset_sum([-1,1,5,4],0) # True subset_sum([-1,1,5,4],-3) # False Secondly, I need to write a solution using what I wrote in the previous solution but now with memoization that uses a dictionary in which the keys are

问题 I will be happy to get some help. I have the following problem: I'm given a list of numbers seq and a target number and I need to write 2 things: A recursive solution that returns True if there is a sum of a subsequence that equals the target number and False otherwise. example: subset_sum([-1,1,5,4],0) # True subset_sum([-1,1,5,4],-3) # False Secondly, I need to write a solution using what I wrote in the previous solution but now with memoization that uses a dictionary in which the keys are