I am inferring that the problem of matching a particular individual's results with haplotypes is a problem in optimization (finding a best fit) with many variab

I am inferring that the problem of matching a particular individual's results with haplotypes is a problem in optimization (finding a best fit) with many variables that is actually solved by maximization (finding a good fit) without doing a comprehensive search of all possible solutions. The space of potential results may be very large -- very many haplotypes from which to select and a percentage to be assigned to each, from 0 to 100, and a perfect result cannot be expected, as ancestors within a given haplotype are nowhere near as similar as identical twins. It is very common, even typical, for algorithms that attempt to find good solutions to such problems to include some randomization (making some guesses based on pseudo-random numbers) followed by more directed attempts to successively improve the guesses previously made. Because some steps of the search are a random walk, different results from the same inputs are common for several iterations of the same algorithm.