ME 366L Weekly Overview - Week 09

ME 366L Weekly Overview - Week 09 - first-order optimality...

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Week Nine – Convex sets and convex programming, first- order optimality conditions, examples of nonlinear programs, classifying problems. Properties and examples of nonlinear programs Context: Convexity plays a large role in understanding the nature of nonlinear programs and in finding global solutions. We discuss its importance and then present first-order necessary conditions that an NLP must satisfy at optimality. Several examples taken from business and engineering are presented and classification scheme is developed to better understand the degree of difficulty associated with a particular NLP. Purpose: To provide you with a solid understanding of convexity, its role in optimization, and the use of
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Unformatted text preview: first-order optimality conditions in finding solutions to NLPs. A second objective is to develop an NLP taxonomy. Objectives: At the end of this lesson, you will be able to: 1. Determine the convexity or concavity of a function, and whether a feasible region is convex. 2. Write out the first-order optimality conditions for a nonlinear program. 3. Explain how NLPs are classified with respect to the nonlinearities in the objective function and constraints. 4. Categorize the degree of difficulty in solving an NLP with respect to the general classification scheme. 5. Set up and solve NLPs with the Excel add-in....
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This note was uploaded on 12/19/2011 for the course M E 366l taught by Professor Staff during the Spring '08 term at University of Texas at Austin.

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