Course objectives and learning outcomes: At the end of the course, the students will

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 and mathematical programming software.

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

3.1. identify and build transportation models.

3.2. identify and build transshipment models.

3.3. identify and build assignment models.

3.4. identify and build network models.

3.5. solve network problems using appropriate algorithms.

4.1. identify and build integer programming models.

5.1. model a sequential decision situation using dynamic programming.

5.2. write recursive functions.

5.3. solve dynamic programming models.