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326   CHAPTER 7 TRANSPORTATION, ASSIGNMENT AND TRANSSHIPMENT PROBLEMS




                      Solution
                      We have an obvious transportation problem where the organization is looking to minimize costs. The relevant
                      costs are a combination of the packing costs and the transportation costs per case. For example the cost of
                      using the Marseille–Capetown route is E2.95 + E1.45, or E4.40 per case. We also note that supply is greater
                      than demand so we will need a dummy destination. Clearly, we could solve this problem in a number of ways.
                      We shall use the MODI method. We shall also solve the problem initially without worrying that all of Marseille’s
                      cases are shipped out. Setting up the transportation tableau and using the minimum cost method to find an
                      initial feasible solution we have:
                            Initial feasible solution: cases transported
                                                       Dar es                    Unused
                            From/To      Capetown      Salaam      Nairobi      (Dummy)       Supply
                            Marseille     200 4.40     100 4.55      0 4.35       100           400
                            Portsmouth    200 4.20        0 5.35    400 3.70        0           600
                            Frankfurt       0 4.25     300 4.25       0 4.80        0           300
                            Capacity      400          400          400           100          1 300

                      The figures in the top right of each cell show the combined cost per case for each route. Because we have a
                      dummy destination, technically their cost coefficients are zero and so we start by allocating cases to one of the
                      dummy cells. So that you can check your own solution, the stages for this solution are:
                         l 100 cases for Marseille–Dummy. All three dummy cells have the same zero cost coefficient so we have
                           made an arbitrary choice. The other two Dummy cells are set to zero.
                         l 400 cases for Portsmouth–Nairobi as this is now the least cost route.
                         l Marseille–Nairobi and Frankfurt–Nairobi cells are set to zero as the maximum capacity for Nairobi is
                           now met.
                         l Next least cost route is Portsmouth–Capetown. Portsmouth is already shipping 400 cases to Nairobi so
                           the remaining 200 cases are allocated to the Portsmouth–Capetown route. The Portsmouth–Dar es
                           Salaam route is set to zero as Portsmouth has now allocated all its 600 cases.
                         l There are now two least cost cells: Frankfurt–Capetown and Frankfurt–Dar es Salaam. The latter has a
                           higher capacity so is preferred and 300 units are allocated to this route. This is all the cases from
                           Frankfurt so Frankfurt–Capetown is set to zero.
                         l This leaves Marseille–Capetown with 200 cases.
                      Total cost of this solution is E4930.
                         We now calculate the u and v values for the current solution, remembering that we must include the Dummy
                      column which has cost coefficients of 0. Here we have:
                                                          u 1 þ v 1 ¼ 4:40
                                                          u 1 þ v 2 ¼ 4:55
                                                          u 1 þ v 4 ¼ 0
                                                          u 2 þ v 1 ¼ 4:20
                                                          u 2 þ v 3 ¼ 3:70
                                                          u 3 þ v 2 ¼ 4:25













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