This course introduces topics in operational research from an engineering perspective. Focuses on practical methods of optimization projects using linear programming. Assignment and midterm questions were easy, but the final was quite difficult and long. The final is also weighted quite heavily so getting a high grade is more difficult.

Introduction: systems theory. Linear Programming: standard form, feasible solutions, graphical method. Simplex Method: tabular form, Big-M Method, infeasible solutions, unbounded variables, implicit constraints. Duality Theory: dual problem, primal-dual relationship, Weak Duality Theory, adapting dual problem to other primal forms, dual simplex method. Sensitivity Analysis: changes in constraints, and coefficients, introducing new variables, and constraints. Transportation Problem: transportation simplex method, Northwest Corner Method, Vogel's Approximation Method, Russel's Approximation Method, unbalanced problems. Assignment Problem: Hungarian Method. Network Analysis: Shortest Route Problem, Minimum Spanning Tree Problem, Maximum Flow Problem, Labelling Method. Project Planning...read more

Writes out his notes live during lecture, which are very clean, rather than rely on power points. Unfortunately, he doesn't post these notes which mean you have to write everything down since the topic summaries he does post are a bit vague. The textbook he recommends is useful but quite opaque without learning the material from him first. He talks slowly, so not every topic was covered in time.

Study assignment and tutorial problems since these problems were on past exams, so are representative. Write good notes since exams are fully open book. Review all the different cases presented in class since assignments only cover a few of them.