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MH3701 Basic Optimisation

Course Summary​

This is a first course in mathematical optimization. It builds the basic knowledge and skills in the theory and techniques of analysing and solving simple optimization models. With these foundations, you will be able to deepen your understanding of more complex optimization models, and their applications to various disciplines in subsequent mathematical optimization and operations research courses.

Learning Outcomes​

At the end of this course, students should be able to:

  1. Solve instances of linear programs with the simplex method.
  2. Explain and relate the geometry, the algebra, and the tabular form of the simplex method.
  3. Solve instances of minimum-cost flow problems with the network simplex method.
  4. Explain the algebra of the network simplex method.
  5. Explain the optimality of a solution to a linear program, and the infeasibility of a linear program, using linear programming duality.
  6. Conduct sensitivity and post-optimality analysis on linear programs.
  7. Solve instances of nonlinear programs via their Karush-Kuhn-Tucker conditions.

Workload​

Very theorectical course. Workload itself is not heavy, but takes a lot of time to understand and practise the concepts.

4 Lab sessions using MatLab. (Each worth 1.5% of final grade)

4 Quizzes (Each worth 5% of final grade)

1 Midterm test worth 24% of final grade

Final Exam worth 50% of final grade

Projects​

Each lab session takes about 2 hours on average. Most can be completed during the dedicated lab session itself. You may have to stay back about 30 mins sometimes to complete it if you are not familiar with MatLab. There are no partial credits given for the labs.

Things to take note of​

Very theoretical, with limited applications. Lots of proofs.

Using a graphing calculator is a REQUIREMENT. Would need to perform many matrix operations throughout the course and during the exam.

If you did not like linear algebra, stay away from this at all costs.

Lecturer provides very nice and concise notes, almost like a textbook.

Conclusion​

Would not recommend, unless you enjoy pure maths.