Optimisation models. One-dimensional search techniques. Unconstrained optimisation techniques for functions with several variables, including search methods using function values only, steepest descent method, Newton's method; quasi-Newton's methods, conjugate gradient methods, accurate and inaccurate line searches, convergence and rate of convergence. Constrained optimisation techniques, including Lagrangian multipliers, Kuhn-Tucker optimality conditions, penalty function methods, quadratic programming techniques, sequential quadratic programming technique. Dynamic programming. Branch and bound methods. -- Course Website
Prerequisites: 8127 (v.6)<br/> Advanced Calculus 201<br/> <br/> or any previous version<br/> <br/> <br/><br/> <br/> OR<br/><br/> <br/> 8648 (v.3)<br/> Mathematical Methods 201<br/> <br/> or any previous version
