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Talk Abstract
Interior-point models: new algorithmic methodology for large-scale constrained optimization

Richard Tapia, Rice University

As applications become more complicated and more demanding we are witnessing an increasing need for algorithms that can handle large optimization problems with a large number of inequality constraints. The standard (classical) approaches are not serving us well. A new methodology for inequality constraints, referred to as interior-point methodology, has recently appeared on the computational methods horizon. In this talk the speaker will give a brief survey of the standard approaches and point out their short-comings. The new interior-point methodology will then be discussed.

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1996-1997 Mathematics in High Performance Computing

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