Nonlinear Optimisation with One or Several Objectives: Kuhn–Tucker Conditions View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2016

AUTHORS

Wolfgang Eichhorn , Winfried Gleißner

ABSTRACT

The chapter starts with a discussion of convex sets and functions in \({ \mathbb{R}}^{n}\) and approximation by quadratic functions. Then it continues with Bellman’s functional equation. For linear regression the method of least squares is used. Next extrema under equality constraints are investigated. We also use envelope theorems and the LeChatelier Principle to determine extrema. The case of inequality constraints is dealt with, too. The chapter ends with an excursion to the Kuhn-Tucker conditions and the optimisation of problems with several objective functions. More... »

PAGES

373-475

Book

TITLE

Mathematics and Methodology for Economics

ISBN

978-3-319-23352-9
978-3-319-23353-6

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-23353-6_8

DOI

http://dx.doi.org/10.1007/978-3-319-23353-6_8

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1043168743


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