Optimization models.

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- Identify the general steps that should be taken in any MS/OR study. Comment on each step.

Problem recognition, observation and formulation: recognize and observe problem, collect data, identify factors that affect the problem, describe it.

Model construction: classify factors as controllable or uncontrollable; develop the model with a structure and parameters.

Solution generation: development and selection process, generating the solution.

Testing and evaluation of solution: run a test data and evaluate if it is acceptable or not.

Implementation: key step in problem solving process, it could be possible to use an implementation-gaming model.

Evaluation: the model most be continually evaluated to determine whether parameter values have change.

- Identify some of the limitations or problems that exist in the field of management science.

Most models consider only one objective function.

The size of the system of equations because many problems in industry, government, or the public sector contain a large number of constrains.

The computational burden.

Cost - benefit.

- Can multiobjective problems be handled with and existing MS/OR technique?

When we have a large set of equations is necessary use some computationally algorithms otherwise the modeling process may be excessive.

- Comment on the cost versus benefit problem as related to an MS/OR project.

Sometimes computerized problem-solving capabilities of management science are adopted without examining the potential benefit that will accrue. Therefore MS must be employed and applied within logical reason.

True/False Questions

- The term management science received its initial impetus with the establishment of The Institute of Management Sciences (TIMS) in 1953.

True

- A scale model is created by visualizing different arrangements and evaluating each alternative.

False

- A descriptive model represents a relationship and indicates a proper course of action.

False

- A normative model may never contain descriptive submodels.

False

- The effectiveness of the model as a function of the decision variables is defined by the objective function.

True

- Given qualities in a model that enable the user to make decisions are referred to as decision variables.

False

- A linear model is one in which all the functional relationships are such that the dependent variable is proportional to the independent variables.

True

- An algorithm is a set of procedures or rules that, when followed in a step-by-step manner, will provide the best solutions to a given model.

True

- Heuristics is a solution process that relies on intuitive and empirical rules to provide and optimal solution to a problem.

True

- A dynamic model is defined as a fixed point in time.

False