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Management Support Systems




                    Notes          management decision. The method consists of priming a visual interactive model of a plant
                                   (or company) with its current status. The model then runs rapidly on a computer, allowing
                                   managers to observe how a plant is likely to operate in the future.
                                   The VIM approach can also be used in conjunction with artificial intelligence.




                                     Notes  Integration of the two techniques adds several capabilities that range from the
                                     ability to build systems graphically to learning about the dynamics of the system.

                                   Self Assessment


                                   Fill in the blanks:
                                   10.  In MSS is a technique for ....................... conducting experiments with a computer on a
                                       model of a management system.

                                   11.  ....................... is a situation with a limited number of events (variables) that can take on
                                       only a finite number of values.
                                   12.  ....................... is the graphical display of computerized results, which may include animation.

                                   13.  Visual Interactive Simulation (VIS) is also known as .......................

                                   5.6 Optimization Via Mathematical Programming

                                   Linear programming (LP) is the best-know technique in family of optimization tools called
                                   mathematical programming. In LP, all relationships among the LP variables are linear.
                                   Mathematical programming is a family of tools designed to help solve managerial problems in
                                   which the decision maker must allocate scarce resources among competing activities to optimize
                                   a measurable goal.
                                   Every LP problem is composed of:

                                       Decision variable – whose values are unknown and are searched for an objective function
                                       – a linear mathematical function that relates the decision variables to the goal, measures
                                       goal attainment, and is to be optimized.

                                       Objective function coefficients – unit profit or cost coefficients indicating the contribution
                                       to the objective of one unit of a decision variable.
                                       Constraints – expressed in the form of linear inequalities or equalities that limit resources
                                       or requirements; these relate the variables through linear relationships.

                                       Capacities – which describe the upper and sometimes lower limits on the constraints and
                                       variables, and
                                       Input/output (technology) coefficients – which indicate resource utilization for a decision
                                       variable.


                                          Example:
                                   An example of modeling in LP is shown below:

                                       The decision variables:
                                       X = units of CC-7
                                         1




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