Authors: Horoba, Christian
Neumann, Frank
Title: Additive approximations of pareto-optimal sets by evolutionary multi-objective algorithms
Language (ISO): en
Abstract: Often the Pareto front of a multi-objective optimization problem grows exponentially with the problem size. In this case, it is not possible to compute the whole Pareto front efficiently and one is interested in good approximations. We consider how evolutionary algorithms can achieve such approximations by using different diversity mechanisms. We discuss some well-known approaches such as the density estimator and the e-dominance approach and point out how and when such mechanisms provably help to obtain good additive approximations of the Pareto-optimal set.
Issue Date: 2008-12
Appears in Collections:Sonderforschungsbereich (SFB) 531

Files in This Item:
File Description SizeFormat 
25708.pdfDNB235.32 kBAdobe PDFView/Open

This item is protected by original copyright

If no CC-License is given, pleas contact the the creator, if you want to use thre resource other than only read it.