Nonlinear Programming (Spring 2004)
15 votes
Free
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This course introduces students to the fundamentals of nonlinear optimization theory and methods. Topics include unconstrained and constrained optimization, linear and quadratic programming, Lagrange and conic duality theory, interior-point algorithms and theory, Lagrangian relaxation, generalized programming, and semi-definite programming. Algorithmic methods used in the class include steepest descent, Newton's method, conditional gradient and subgradient optimization, interior-point methods and penalty and barrier methods. Starts :
2004-02-01 |
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AlternativesIf you know any alternatives, please let us know. PrerequisitesIf you can suggest any prerequisite, please let us know. Certification Exams-- there are no exams to get certification after this course --If your company does certification for those who completed this course then register your company as certification vendor and add your exams to the Exams Directory. | ||
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