-

 

 

 




Optimization Online





 

An Efficient Interior-Point Method for Convex Multicriteria Optimization Problems

Joerg Fliege (fliege***at***math.uni-dortmund.de)

Abstract: In multicriteria optimization, several objective functions, conflicting with each other, have to be minimized simultaneously. We propose a new efficient method for approximating the solution set of a multiobjective programming problem, where the objective functions involved are arbitary convex functions and the set of feasible points is convex. The method is based on generating warm-start points for an efficient interior-point algorithm, while the approximation computed consists of a finite set of discrete points. Complexity results for the method proposed are derived. It turns out that the number of operations per point \emph{decreases} when the number of points generated for the approximation \emph{increases}.

Keywords: multicriteria, vector optimization, interior-point, selfconcordant, warm-start

Category 1: Other Topics (Multi-Criteria Optimization )

Category 2: Convex and Nonsmooth Optimization (Convex Optimization )

Citation: Ergebnisberichte Angewandte Mathematik, Nr.~248. Fachbereich Mathematik, Universit{\

Download: [PDF]

Entry Submitted: 03/09/2004
Entry Accepted: 03/19/2004
Entry Last Modified: 03/09/2004

Modify/Update this entry


  Visitors Authors More about us Links
  Subscribe, Unsubscribe
Digest Archive
Search, Browse the Repository

 

Submit
Update
Policies
Coordinator's Board
Classification Scheme
Credits
Give us feedback
Optimization Journals, Sites, Societies
Mathematical Programming Society