67,165 research outputs found

    Job-shop scheduling with an adaptive neural network and local search hybrid approach

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    This article is posted here with permission from IEEE - Copyright @ 2006 IEEEJob-shop scheduling is one of the most difficult production scheduling problems in industry. This paper proposes an adaptive neural network and local search hybrid approach for the job-shop scheduling problem. The adaptive neural network is constructed based on constraint satisfactions of job-shop scheduling and can adapt its structure and neuron connections during the solving process. The neural network is used to solve feasible schedules for the job-shop scheduling problem while the local search scheme aims to improve the performance by searching the neighbourhood of a given feasible schedule. The experimental study validates the proposed hybrid approach for job-shop scheduling regarding the quality of solutions and the computing speed

    Cluster Structure in Cosmological Simulations I: Correlation to Observables, Mass Estimates, and Evolution

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    We use Enzo, a hybrid Eulerian AMR/N-body code including non-gravitational heating and cooling, to explore the morphology of the X-ray gas in clusters of galaxies and its evolution in current generation cosmological simulations. We employ and compare two observationally motivated structure measures: power ratios and centroid shift. Overall, the structure of our simulated clusters compares remarkably well to low-redshift observations, although some differences remain that may point to incomplete gas physics. We find no dependence on cluster structure in the mass-observable scaling relations, T_X-M and Y_X-M, when using the true cluster masses. However, estimates of the total mass based on the assumption of hydrostatic equilibrium, as assumed in observational studies, are systematically low. We show that the hydrostatic mass bias strongly correlates with cluster structure and, more weakly, with cluster mass. When the hydrostatic masses are used, the mass-observable scaling relations and gas mass fractions depend significantly on cluster morphology, and the true relations are not recovered even if the most relaxed clusters are used. We show that cluster structure, via the power ratios, can be used to effectively correct the hydrostatic mass estimates and mass-scaling relations, suggesting that we can calibrate for this systematic effect in cosmological studies. Similar to observational studies, we find that cluster structure, particularly centroid shift, evolves with redshift. This evolution is mild but will lead to additional errors at high redshift. Projection along the line of sight leads to significant uncertainty in the structure of individual clusters: less than 50% of clusters which appear relaxed in projection based on our structure measures are truly relaxed.Comment: 57 pages, 18 figures, accepted to ApJ, updated definition of T_X and M_gas but results unchanged, for version with full resolution figures, see http://www.ociw.edu/~tesla/sims.ps.g

    Compensatory evolution and the origins of innovations

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    Cryptic genetic sequences have attenuated effects on phenotypes. In the classic view, relaxed selection allows cryptic genetic diversity to build up across individuals in a population, providing alleles that may later contribute to adaptation when co-opted - e.g. following a mutation increasing expression from a low, attenuated baseline. This view is described, for example, by the metaphor of the spread of a population across a neutral network in genotype space. As an alternative view, consider the fact that most phenotypic traits are affected by multiple sequences, including cryptic ones. Even in a strictly clonal population, the co-option of cryptic sequences at different loci may have different phenotypic effects and offer the population multiple adaptive possibilities. Here, we model the evolution of quantitative phenotypic characters encoded by cryptic sequences, and compare the relative contributions of genetic diversity and of variation across sites to the phenotypic potential of a population. We show that most of the phenotypic variation accessible through co-option would exist even in populations with no polymorphism. This is made possible by a history of compensatory evolution, whereby the phenotypic effect of a cryptic mutation at one site was balanced by mutations elsewhere in the genome, leading to a diversity of cryptic effect sizes across sites rather than across individuals. Cryptic sequences might accelerate adaptation and facilitate large phenotypic changes even in the absence of genetic diversity, as traditionally defined in terms of alternative alleles

    Characterizing Galaxy Clusters with Gravitational Potential

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    We propose a simple estimator for the gravitational potential of cluster-size halos using the temperature and density profiles of the intracluster gas based on the assumptions of hydrostatic equilibrium and spherical symmetry. Using high resolution cosmological simulations of galaxy clusters, we show that the scaling relation between this estimator and the gravitational potential has a small intrinsic scatter of ~8%-15%, and it is insensitive to baryon physics outside the cluster core. The slope and the normalization of the scaling relation vary weakly with redshift, and they are relatively independent of the choice of radial range used and the dynamical states of the clusters. The results presented here provide a possible way for using the cluster potential function as an alternative to the cluster mass function in constraining cosmology using galaxy clusters.Comment: 10 pages, 7 figures, 4 tables. Matching the version accepted for publication in the Astrophysical Journa
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