TAOP24 Optimization, Advanced Course 2011

Study Guide@lith

Valid for year : 2011

TAOP24	Optimization, Advanced Course, 6 ECTS credits. /Optimeringslära fortsättningskurs/ For: CS Mat Y
	Prel. scheduled hours: 60 Rec. self-study hours: 100
	Area of Education: Science Main field of studies: Mathematics, Applied Mathematics,
	Advancement level (G1, G2, A): G2
	Aim: Optimization deals with mathematical theory and methods aiming at analyzing and solving decision problems that arise in technology, economy, medicine, etc. The course gives a broad orientation of the field of optimization, with emphasis on basic theory and methods for continuous and discrete optimization problems in finite dimension, and it also gives some insight into its use for analyzing practical optimization problems. After the course, the student shall: be able to identify optimization problems and classify them according to their properties, into, for example, linear and nonlinear, or continuous and discrete, problems construct mathematical models of simple optimization problems be able to define and use basic concepts, such as, for example, local and global optimality, convexity, weak and strong duality, and valid inequalities have knowledge about and be able to apply basic theory for some common types of optimization problems, such as, for example, duality theory for linear optimization problems, and have knowledge about and be able to use optimality conditions, such as, for example, Bellman's equations, to determine the optimality of a given solution have knowledge about and be able to apply basic principles for solving some common types of optimization problems, such as, for example, branch-and-bound for discrete problems be able to use relaxations, and especially Lagrangian duality, to approximate optimization problems, and be able to estimate the optimal objective value through lower and upper bounds be able to use commonly available software for solving optimization problems of standard type have some knowledge of practical applications of optimization
	Prerequisites: (valid for students admitted to programmes within which the course is offered) Introduction to optimization. Note: Admission requirements for non-programme students usually also include admission requirements for the programme and threshhold requirements for progression within the programme, or corresponding.
	Supplementary courses: Mathematical optimization.
	Organisation: Lectures which include theory, problem solving and applications. Exercises which are intended to give individual training in problem solving. A laboratory course with emphasis on modelling and the use of optimization software.
	Course contents: Fundamental concepts within optimization, such as mathematical modelling, optimality conditions, convexity, sensitivity analysis, duality, and Lagrangean relaxation. Basic theory and methods for linear and nonlinear optimization, and integer and network optimization.
	Course literature: Jan Lundgren, Mikael Rönnqvist & Peter Värbrand - Optimeringslära (Studentlitteratur, 2008) - Jan Lundgren, Mathias Henningsson & Mikael Rönnqvist - Optimeringslära övningsbok (Studentlitteratur, 2008)
	Examination:
	Written examination Labratory course	4 ECTS 2 ECTS


Course language is English. Department offering the course: MAI. Director of Studies: Torbjörn Larsson Examiner: Oleg Burdakov Link to the course homepage at the department Course Syllabus in Swedish

Linköping Institute of Technology
Contact: TFK , val@tfk.liu.se Last updated: 02/13/2012