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Publication Details for Article "Comparison of Multiobjective Evolutionary Algorithms: Empirical Results"

 

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Authors: Eckart Zitzler, Kalyanmoy Deb, Lothar Thiele
Group: Computer Engineering
Type: Article
Title: Comparison of Multiobjective Evolutionary Algorithms: Empirical Results
Year: 2000
Month: April
Pub-Key: ZDT00c
Journal: Evolutionary Computation
Volume: 8
Number: 2
Pages: 173-195
Keywords: EMO
Abstract: In this paper, we provide a systematic comparison of various evolutionary approaches to multiobjective optimization using six carefully chosen test
functions. Each test function involves a particular feature that is known to
cause difficulty in the evolutionary optimization process, mainly in converging
to the Pareto-optimal front (e.g., multimodality and deception). By
investigating these different problem features separately, it is possible to
identify the kind of problems to which a certain technique is well suited or
not. However, in contrast to what was suspected beforehand, the experimental
results indicate a hierarchy of the algorithms under consideration. Furthermore,
the emerging effects give evidence that the suggested test functions provide
sufficient complexity to compare multiobjective optimizers. Finally, elitism is
shown to be an important factor for improving evolutionary multiobjective
search.
Resources: [BibTeX] [Paper as PDF]

 

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