Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICCIS.2006.252330
Title: An investigation on noisy environments in evolutionary multi-objective optimization
Authors: Goh, C.K.
Chiam, S.C.
Tan, K.C. 
Keywords: Multi-objective evolutionary algorithms
Noise
Issue Date: 2006
Source: Goh, C.K.,Chiam, S.C.,Tan, K.C. (2006). An investigation on noisy environments in evolutionary multi-objective optimization. 2006 IEEE Conference on Cybernetics and Intelligent Systems : -. ScholarBank@NUS Repository. https://doi.org/10.1109/ICCIS.2006.252330
Abstract: In addition to the need of satisfying several competing objectives, many real-world applications are also characterized by a certain degree of noise, manifesting itself in the form of signal distortion or uncertain information. While studies have shown that many multi-objective evolutionary optimizers are capable of achieving optimization goals, their ability to deal with noise is rarely studied. In this paper, extensive studies are carried out to examine the impact of noisy environments in evolutionary multi-objective optimization based upon five benchmark problems characterized by different difficulties in local optimality, non-uniformity, discontinuity and non-convexity. Interestingly, the baseline algorithm employed tends to evolve better solution sets in the presence of low noise levels for some problems. Nevertheless, the evolutionary optimization process degenerates into random search under increasing noise levels. © 2006 IEEE.
Source Title: 2006 IEEE Conference on Cybernetics and Intelligent Systems
URI: http://scholarbank.nus.edu.sg/handle/10635/69340
ISBN: 1424400236
DOI: 10.1109/ICCIS.2006.252330
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