Maximizing Sum of Weights w/ N Entities & M Constraints

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The discussion revolves around maximizing a function involving N entities, each with a weight and similarity coefficients, under M constraints where M is less than N. The goal is to maximize the sum of weights divided by the sum of similarity coefficients for unique combinations of entities. The user seeks an efficient algorithm to handle larger values of N (around 50) and M (about 5), as manual enumeration becomes impractical. Suggestions for potential algorithms or programming approaches to solve this optimization problem are requested. The thread emphasizes the need for computational solutions to manage the complexity of the calculations.
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Hi. I have a problem I am hoping you all can shed some light on.

I have N entities, O, each described by N values - a weight W and N-1 similarity coefficients to the other N-1 entities. I guess we can represent Oi as (Wi, Sij, j=(1,2,...,N, i!=j)(?).

Given an integer M and M < N I need to maximize the following function:
Sumi(Wi/Sumj(Sij, j=(1,2,...,N), i!=j))
where i and j in the sums are constrained to the unique combinations of the integers 1 to N of size M.
As an example let N=4, M=3 there are then 4 unique combinations of the numbers 1,2,3,4 of size 3: (1,2,3), (1,2,4), (1,3,4) and (2,3,4). The values for the function are therefore:
W1/(S1,2+S1,3)+W2/(S2,1+S2,3)+W3/(S3,1+S3,2)
W1/(S1,2+S1,4)+W2/(S2,1+S2,4)+W4/(S4,1+S4,2)
W1/(S1,3+S1,4)+W3/(S3,1+S3,4)+W4/(S4,1+S4,3)
W2/(S2,3+S2,4)+W3/(S3,2+S3,4)+W4/(S4,2+S4,3).

For small N and M I can enumerate the combinations and calculate the maximum sum but my problem has N~50 and M~5.

Any suggestions or thoughts of an akgorithm to calulate the max? I hope I have made it clear.

Thanks in advance.
 
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