Advances in convex optimization: conic programming

• Autores: Arkadi Nemirovski
• Localización: Proceedings oh the International Congress of Mathematicians: Madrid, August 22-30,2006 : invited lectures / coord. por Marta Sanz Solé, Javier Soria de Diego, Juan Luis Varona Malumbres, Joan Verdera, Vol. 1, 2006, ISBN 978-3-03719-022-7, págs. 413-444
• Idioma: inglés
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• Resumen

  • During the last two decades, major developments in convex optimization were focusing on conic programming, primarily, on linear, conic quadratic and semidefinite optimization.

    Conic programming allows to reveal rich structure which usually is possessed by a convex program and to exploit this structure in order to process the program efficiently. In the paper, we overview the major components of the resulting theory (conic duality and primal-dual interior point polynomial time algorithms), outline the extremely rich �expressive abilities� of conic quadratic and semidefinite programming and discuss a number of instructive applications.