First time poster...apologies for formatting.
I am trying to devise a solution to a familiar linear algebra equation, Ax=b, where all elements in A are non-negative and all the elements in b are positive. My constraint is that the difference between the L1 norm of Ax and L1 norm of b must be minimized (ie min (||Ax||_1 - ||b||_1)). In english, I want the coefficients that make the sum of the elements in b "closest" to the sum of the elements in Ax.
Hoping to find out whether there is an algorithmic solution to this problem, preferably in Python.