Optimization

School / Prep
ENSEIRB-MATMECA

Internal code

ET5MA118

Description

The aim of this course is to present the basic concepts and results of optimization theory, as well as some classic algorithms for finding the optimum.

CMLectures6,66h
TDTutorial2,66h
TIIndividual work23h
PRACTICAL WORKPractical work13,33h

Mandatory prerequisites

Elements of mathematics at 1st cycle level (IUT, DEUG, Prépa)

Syllabus

Part I: Introduction to optimizationI - Definition and backgroundII - Application examplesIII - Mathematical background A - Differential calculus B - Properties: convexity, coercivityPart II: Iterative optimization methodsI - Optimality conditionsII - Principle of descent methodsIII - Convergence conditionsIV - Some classic algorithms: Gauss-Seidel, gradient descent, Newton, Gauss-Newton.Part III: Optimization under constraintsI - Definition and conceptsII - Case of equality constraintsIII - Case of inequality constraintsIV - Equality and inequality constraints

Further information

Applied mathematics

Initial assessment / Main session

Type of assessment	Nature of assessment	Duration (in minutes)	Number of tests	Evaluation coefficient	Eliminatory evaluation mark	Remarks
Final inspection	Written	90		0.5		without document without calculator
Continuous control	Minutes			0.5

Second chance / Catch-up session

Type of assessment	Nature of assessment	Duration (in minutes)	Number of tests	Evaluation coefficient	Eliminatory evaluation mark	Remarks
Final test	Written	90		0.75		without document without calculator
Continuous control	Minutes			0.25		Carryover of session 1 mark