MTH3330 Optimisation and operations research

When you finish this unit, you should be able to:

1. 1

   Demonstrate an understanding of necessary and sufficient optimality conditions for optimisation problems;

2. 2

   Demonstrate an understanding of the mathematical principles behind common iterative algorithms for solving unconstrained nonlinear optimisation problems;

3. 3

   Formulate as an optimisation problem the task of training a machine learning model and select an appropriate optimisation algorithm;

4. 4

   Demonstrate an understanding of Lagrangian duality and the use of non-smooth optimisation methods to solve Lagrangian dual problems.

5. 5

   Formulate a range of operations research problems as linear programming problems, and solve them computationally;

6. 6

   Demonstrate an understanding how the most widely used linear programming algorithms work;

7. 7

   Apply duality theory to prove optimality of a solution of a linear programming problem;

8. 8

   Solve network optimisation problems with specialised algorithms.