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114   CHAPTER 3 LINEAR PROGRAMMING: SENSITIVITY ANALYSIS AND INTERPRETATION OF SOLUTION



                      MANAGEMENT SCIENCE IN ACTION



                      The Nutricia Dairy and Drinks Group, Hungary
                          ince the early 1990s, much of what used to be  central collection points; transportation costs
                      S called Eastern Europe has been undergoing  involved in shipping the milk from the central col-
                      major economic, political and social transformation  lection points to the plants; production costs;
                      moving from the old Soviet Union command econ-  inter-plant costs incurred when semi-finished prod-
                      omy into market economies. This has meant major  ucts are shipped from one plant to another; trans-
                      efforts to improve performance and economic effi-  portation costs to the distribution centres; ware-
                      ciency. The Nutricia Dairy and Drinks group (NDDG)  housing costs involved in storing products at the
                      started acquiring dairy companies in Hungary in  distribution centres. NDDG developed an LP
                      1995 and has been using linear programming to  model to minimize total costs but was particularly
                      help it improve efficiency and also to undertake sce-  interested in using the model to undertake sce-
                      nario planning using sensitivity analysis.  nario planning – looking at a variety of strategic
                         The overall structure of NDDG’s business is as  options for rationalizing the supply side of the
                      follows. Its nine plants are supplied with raw milk  business. The sensitivity findings include the
                      by over 400 farmers throughout Hungary. The  following:
                      plants produce a range of dairy and dairy-related
                                                                  • A change in production costs of up to 10 per cent
                      products – over 300 different products in total.
                                                                    had no impact on the optimal solution.
                      Some products are produced at individual plants.
                      Other products are semi-finished at one plant and  • An increase of 5 per cent in milk transportation
                      then shipped to another plant to be turned into  costs would make the opening of three new
                      fully finished products. The plant output is sent to  plants cost-effective.
                      17 distribution centres which in turn supply over  • Changes in inter-plant costs had no effect on the
                      17 000 shops. NDDG had identified a number of  optimal solution.
                      major costs in its operations. First, milk collection
                                                                  Based on FHE. Wouda, P van beck, JGAJ. van der Vorst and H. Tacke,
                      costs incurred in collecting from individual farms  ‘An application of mixed-integer linear programming models on the
                      (which range from supplying only 20 000 litres a  redesign of the supply network of Nutricia Dairy and Drinks Group in
                      year to those supplying around 11 million litres) to  Hungary’, OR Spectrum 24/4 (Nov. 2002): 449–465.



                                       Suppose that management is willing to reconsider their position regarding the
                                     maximum weight of the daily diet. The dual price of 91.92 for constraint 4 shows that
                                     a one-unit increase in the right-hand side of constraint 4 will reduce total cost by
                                     91.92 sh. The RIGHT HAND SIDE RANGES section of the output shows that this
                                     interpretation is valid for increases in the right-hand side up to a maximum of 8.478
                                     kilos. Thus, the effect of increasing the right-hand side of constraint 4 from six to
                                     eight kilos is a decrease in the total daily cost of 2   91.92 or 183.84 sh. Keep in mind
                                     that if this change were made, the feasible region would change, and we would
                                     obtain a new optimal solution.
                                       The OBJECTIVE COEFFICIENT RANGES section of the computer output
                                     shows a lower limit of  39.29 for S. Clearly, in a real problem, the objective function
                                     coefficient of S (the cost of the standard product) cannot take on a negative value.
                                     So, from a practical point of view, we can think of the lower limit for the objective
                                     function coefficient of S as being zero. We can thus conclude that no matter how
                                     much the cost of the standard mix were to decrease, the optimal solution would not
                                     change. Even if KCC could obtain the standard product for free, the optimal
                                     solution would still specify a daily diet of 3.51 kilos of the standard product, 0.95
                                     kilos of the enriched product and 1.54 kilos of the vitamin and mineral feed additive.
                                     However, any decrease in the per-unit cost of the standard feed would result in a
                                     decrease in the total cost for the optimal daily diet.




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