<![CDATA[MoneyScience: MIT OpenCourseWare - Nonlinear Programming, Spring 2004]]>
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http://www.moneyscience.com/pg/bookmarks/Admin/read/48820/mit-opencourseware-nonlinear-programming-spring-2004Fri, 29 Jul 2011 06:15:44 -0500
http://www.moneyscience.com/pg/bookmarks/Admin/read/48820/mit-opencourseware-nonlinear-programming-spring-2004
<![CDATA[MIT OpenCourseWare - Nonlinear Programming, Spring 2004]]>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.
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