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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.

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Teaching hours

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

Mandatory prerequisites

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

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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

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Further information

Applied mathematics

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Assessment of knowledge

Initial assessment / Main session - Tests

Type of assessmentType of testDuration (in minutes)Number of testsTest coefficientEliminatory mark in the testRemarks
Final inspectionWritten900.5without document without calculator
Continuous controlMinutes0.5

Second chance / Catch-up session - Tests

Type of assessmentType of testDuration (in minutes)Number of testsTest coefficientEliminatory mark in the testRemarks
Final testWritten900.75without document without calculator
Continuous controlMinutes0.25Carryover of session 1 mark