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- W2034272052 abstract "A novel self-adaption strategy for the parameter epsiv in epsiv-MOEA is proposed in this paper based on the analyses of the relationship between the value of epsiv and the maximum number of non-dominated solutions. Then this novel strategy is applied in epsiv-MOEA and tested on 10 common benchmark functions. The experimental results demonstrate that even if without the good initial value for the parameter s, epsiv-MOEA with this self-adaption strategy (named Algorithm 1) is able to approximately obtain the expected number of non-dominated solutions, which are very close to and uniformly distributed on the Pareto-optimal front. Furthermore, the genetic drift phenomenon in Algorithm 1 is discussed Two cases of genetic drift are pointed out, and one case can be fixed up by a simple approach proposed in this paper." @default.
- W2034272052 created "2016-06-24" @default.
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- W2034272052 date "2008-06-01" @default.
- W2034272052 modified "2023-09-23" @default.
- W2034272052 title "The self-adaption strategy for parameter ε in ε-MOEA" @default.
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- W2034272052 doi "https://doi.org/10.1109/cec.2008.4631194" @default.
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