178,980 research outputs found

    Explicit memory schemes for evolutionary algorithms in dynamic environments

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    Copyright @ 2007 Springer-VerlagProblem optimization in dynamic environments has atrracted a growing interest from the evolutionary computation community in reccent years due to its importance in real world optimization problems. Several approaches have been developed to enhance the performance of evolutionary algorithms for dynamic optimization problems, of which the memory scheme is a major one. This chapter investigates the application of explicit memory schemes for evolutionary algorithms in dynamic environments. Two kinds of explicit memory schemes: direct memory and associative memory, are studied within two classes of evolutionary algorithms: genetic algorithms and univariate marginal distribution algorithms for dynamic optimization problems. Based on a series of systematically constructed dynamic test environments, experiments are carried out to investigate these explicit memory schemes and the performance of direct and associative memory schemes are campared and analysed. The experimental results show the efficiency of the memory schemes for evolutionary algorithms in dynamic environments, especially when the environment changes cyclically. The experimental results also indicate that the effect of the memory schemes depends not only on the dynamic problems and dynamic environments but also on the evolutionary algorithm used

    Primal-dual genetic algorithms for royal road functions

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    Copyright @ 2002 IFACBased on Holland's simple genetic algorithm (SGA) three have been many variations developed. Inspired by the phenomenon of diploid genotype and deminance mechanisms broadly existing in nature, we have proposed a primal-dual genetic algorithm (PDGA), see (Yang 2002). Our preliminary experiments based on the Royal Road functions have shown that PDGA outperforms SGA for different performance measures. In this paper, we present some further experiment results, especially onthe dynamic performance of PDGA over SGA, and give out our explanations and analyses about ehy PDGA outperforms SGA based on these results. Through the primal-dual mapping between a pair of chromosomes, PDGA's performance of exploration in the search space, especially during the early generations, is improved and thus its total searching efficiency is improved

    Population-based incremental learning with memory scheme for changing environments

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    Copyright @ 2005 ACMIn recent years there has been a growing interest in studying evolutionary algorithms for dynamic optimization problems due to its importance in real world applications. Several approaches have been developed, such as the memory scheme. This paper investigates the application of the memory scheme for population-based incremental learning (PBIL) algorithms, a class of evolutionary algorithms, for dynamic optimization problems. A PBIL-specific memory scheme is proposed to improve its adaptability in dynamic environments. In this memory scheme the working probability vector is stored together with the best sample it creates in the memory and is used to reactivate old environments when change occurs. Experimental study based on a series of dynamic environments shows the efficiency of the memory scheme for PBILs in dynamic environments. In this paper, the relationship between the memory scheme and the multipopulation scheme for PBILs in dynamic environments is also investigated. The experimental results indicate a negative interaction of the multi-population scheme on the memory scheme for PBILs in the dynamic test environments

    Hierarchical majorana neutrinos from democratic mass matrices

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    In this paper, we obtain the light neutrino masses and mixings consistent with the experiments, in the democratic texture approach. The essential ansatz is that νRi\nu_{Ri} are assumed to transform as "right-handed fields" 2R+1R\bf 2_{R} + 1_{R} under the S3L×S3RS_{3L} \times S_{3R} symmetry. The symmetry breaking terms are assumed to be diagonal and hierarchical. This setup only allows the normal hierarchy of the neutrino mass, and excludes both of inverted hierarchical and degenerated neutrinos. Although the neutrino sector has nine free parameters, several predictions are obtained at the leading order. When we neglect the smallest parameters ζν\zeta_{\nu} and ζR\zeta_{R}, all components of the mixing matrix UPMNSU_{\rm PMNS} are expressed by the masses of light neutrinos and charged leptons. From the consistency between predicted and observed UPMNSU_{\rm PMNS}, we obtain the lightest neutrino masses m1m_{1} = (1.1 \to 1.4) meV, and the effective mass for the double beta decay \vev{m_{ee}} \simeq 4.5 meV.Comment: 14 pages, 1 table, substantially revised versio
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