
Academic Year:  2016/7 
Owning Department/School:  Department of Mathematical Sciences 
Credits:  6 [equivalent to 12 CATS credits] 
Notional Study Hours:  120 
Level:  Masters UG & PG (FHEQ level 7) 
Period: 

Assessment Summary:  CW 25%, EX 75% 
Assessment Detail: 

Supplementary Assessment: 

Requisites:  Before taking this module you must take MA20218 AND take MA20222 
Description:  Aims: To teach an understanding of iterative methods for nonlinear equations and optimisation. Learning Outcomes: Students should know a range of modern iterative methods for solving nonlinear systems and optimisation problems. They should be able to analyse their algorithms and should have an understanding of relevant practical issues and their importance in a range of application areas. Skills: Problem Solving (T,F&A), Computing (T,F&A), independent study and report writing. Content: Topics will be chosen from the following: Solution methods for nonlinear equations: Newton's method. Computation of solution paths. Pseudoarc length continuation. Unconstrained Optimisation: Line search vs trust region methods. QuasiNewton and nonlinear conjugate gradient. Linear and nonlinear least squares. Constrained Optimisation: Optimality conditions, KKT systems, numerical methods for constrained optimisation, linear and nonlinear programming. Largescale systems: A motivating example from PDEconstrained optimisation. Reducedorder models (e.g., SVDbased methods) and sparse linear systems (e.g., iterative methods and preconditioners). 
Programme availability: 
MA40050 is Optional on the following programmes:Department of Mathematical Sciences

Notes:
