It computes an approximate solution to an one-dimensional knapsack problem. In textbooks it is typically posed as finding a maximum lower than the size of the knapsack (to minimize the empty space). Here it is inverted: the goal is to find minimum higher than the size of the knapsack (to minimize the change required).

Whatever you do, don't reinvent the wheel, there's a rich literature on this problem.