A Multiobjective Evolutionary Algorithm Guided by Averaged Hausdorff Distance to Aspiration Sets

Rudolph G, Schütze O, Grimme C, Trautmann H


Abstract
The incorporation of expert knowledge into multiobjective optimization is an important issue which in this paper is reflected in terms of an aspiration set consisting of multiple reference points. The behaviour of the recently introduced evolutionary multiobjective algorithm AS-EMOA is analysed in detail and comparatively studied for biobjective optimization problems w.r.t. R-NSGA2 and a respective variant. It will be shown that the averaged Hausdorff distance, integrated into AS-EMOA, is an effcient means to accurately approximate the desired aspiration set.

Keywords
multi-objective optimization; aspiration set; preferences



Publication type
Chapter in Book

Peer reviewed
Yes

Publication status
Published

Year
2014

Book title
EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation V

Editor
Tantar A, Tantar E, Sun J, Zhang W, Ding Q, Schütze O, Emmerich M, Legrand P, Del Moral P, Coello Coello CA

Pages range
261-273

Volume
288

Title of series
Advances in Intelligent Systems and Computing

Publisher
Springer International Publishing

Language
English

ISBN
978-3-319-07493-1

DOI

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