Indicator-Based Selection in Multiobjective Search View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2004

AUTHORS

Eckart Zitzler , Simon Künzli

ABSTRACT

This paper discusses how preference information of the decision maker can in general be integrated into multiobjective search. The main idea is to first define the optimization goal in terms of a binary performance measure (indicator) and then to directly use this measure in the selection process. To this end, we propose a general indicator-based evolutionary algorithm (IBEA) that can be combined with arbitrary indicators. In contrast to existing algorithms, IBEA can be adapted to the preferences of the user and moreover does not require any additional diversity preservation mechanism such as fitness sharing to be used. It is shown on several continuous and discrete benchmark problems that IBEA can substantially improve on the results generated by two popular algorithms, namely NSGA-II and SPEA2, with respect to different performance measures. More... »

PAGES

832-842

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-540-30217-9_84

DOI

http://dx.doi.org/10.1007/978-3-540-30217-9_84

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1006836276


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