I edited the post to add more detail.

It’s definitely more efficient to test points from high values to lows. For example, you always want to test point (5,8) before you test point (4,7) because if the former passes there’s no need to test the latter. But beyond that I’m lost on how to improve the efficiency of the search.

I'm looking for advice on how to efficiently search a solution space under certain conditions. The solution space is a multidimensional array of positive integers. At each point in the array I run a function that either fails or passes. Importantly, if a point passes, then every point "under" it will also pass and doesn't need to be tested. To illustrate, a 2D example would be an array of X and Y where X is 0 - 10 and Y is 0 - 15. If the point (2,3) passes then I know that (2,2), (2,1), (2,0), (1,3), (1,2), (1,1), (1,0), (0,3), (0,2) (0,1), (0,0) will also pass. Each of those points is "under" (2,3) in the sense that each element is less than or equal to it. There can be multiple “upper” pass points - for example, (1,5) could be a pass point in addition to (2,3). I've already gleaned that it's more efficient to search the solution space from high to low values, because if an "upper" point passes then there's no need to test the "lower" points. But any advice beyond that is greatly appreciated, thank you!