1.1. describe steps of model building process.

1.2. define assumptions of linear programming models.

1.3. identify application areas of linear programming.

2.1. define parameters, decision variables, objectives and constraints.

2.2. develop linear programming models.

2.3. solve linear programming models and make sensitivity analysis using the graphical method.

2.4. solve linear programming models using the simplex method and perform sensitivity analysis.

2.5. identify the relation between the primal and the dual problems.

3.1. identify efficient solutions.

3.2. use goal programming to solve multi-criteria decision making problems.

3.3. identify relevant costs in a decision making problem.

3.4. select among alternative courses of actions.

4.1. find the optimal strategies and the values of two-person constant-sum games.

4.2. find the equilibrium points for two-person nonconstant-sum games.

4.3. use the core and the Shapley value for n-person games.

5.1. solve linear programming models using software.

5.2. perform sensitivity analysis using software output.

5.3. select among alternative courses of actions.