Scalar and Vector Optimization with Composed Objective Functions and Constraints

Nicole Lorenz () and Gert Wanka ()
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Nicole Lorenz: Chemnitz University of Technology
Gert Wanka: Chemnitz University of Technology

A chapter in Optimization, Simulation, and Control, 2013, pp 107-130 from Springer

Abstract: Abstract In this chapter we consider scalar and vector optimization problems with objective functions being the composition of a convex function and a linear mapping and cone and geometric constraints. By means of duality theory we derive dual problems and formulate weak, strong, and converse duality theorems for the scalar and vector optimization problems with the help of some generalized interior point regularity conditions and consider optimality conditions for a certain scalar problem.

Keywords: Duality; Interior point regularity condition; Optimality conditions (search for similar items in EconPapers)
Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:spr:spochp:978-1-4614-5131-0_8

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DOI: 10.1007/978-1-4614-5131-0_8

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