1. Introduction and optimization basics 2. Linear programming (LP) 3. Mixed-integer linear programming (MILP) 4. Nonlinear programming (NLP) and dynamic optimization (DO) 5. Mixed-integer nonlinear programming (MINLP) and deterministic global optimization 6. Stochastic programming 7. Robust optimization 8. Optimization and big data analytics 9. Computation