In our case, column B now has the greatest difference, which is 3. We assign 200 units to the low- est-cost square in column B that has not been crossed out. This is seen to be E–B. Since B’s require- ments have now been met, we place an X in the F–B square to eliminate it. Differences are once again recomputed. This process is summarized in Table T4.7. The greatest difference is now in row E. Hence, we shall assign as many units as possible to the lowest-cost square in row E, that is, E–C with a cost of $3. The maximum assignment of 100 units depletes the remaining availability at E. The square E–A may therefore be crossed out. This is illus- trated in Table T4.8. The final two allocations, at F–A and F–C, may be made by inspecting supply restrictions (in the rows) and demand requirements (in the columns). We see that an assignment of 200 units to F–A and 100 units to F–C completes the table (see Table T4.9). The cost of this VAM assignment is = (100 units × $5) + (200 units × $4) + (100 units × $3) + (200 units × $9) + (100 units × $5) = $3,900. It is worth noting that the use of Vogel’s approximation method on the Arizona Plumbing Corporation data produces the optimal solution to this problem. Even though VAM takes many more calculations to find an initial solution than does the northwest corner rule, it almost always produces a much better initial solution. Hence VAM tends to minimize the total number of compu- tations needed to reach an optimal solution.