204,387 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

    Global Thresholding and Multiple Pass Parsing

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    We present a variation on classic beam thresholding techniques that is up to an order of magnitude faster than the traditional method, at the same performance level. We also present a new thresholding technique, global thresholding, which, combined with the new beam thresholding, gives an additional factor of two improvement, and a novel technique, multiple pass parsing, that can be combined with the others to yield yet another 50% improvement. We use a new search algorithm to simultaneously optimize the thresholding parameters of the various algorithms.Comment: Fixed latex errors; fixed minor errors in published versio

    IMPROVING MOLECULAR FINGERPRINT SIMILARITY VIA ENHANCED FOLDING

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    Drug discovery depends on scientists finding similarity in molecular fingerprints to the drug target. A new way to improve the accuracy of molecular fingerprint folding is presented. The goal is to alleviate a growing challenge due to excessively long fingerprints. This improved method generates a new shorter fingerprint that is more accurate than the basic folded fingerprint. Information gathered during preprocessing is used to determine an optimal attribute order. The most commonly used blocks of bits can then be organized and used to generate a new improved fingerprint for more optimal folding. We thenapply the widely usedTanimoto similarity search algorithm to benchmark our results. We show an improvement in the final results using this method to generate an improved fingerprint when compared against other traditional folding methods

    Dynamics of Lennard-Jones clusters: A characterization of the activation-relaxation technique

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    The potential energy surface (PES) of Lennard-Jones clusters is investigated using the activation-relaxation technique (ART). This method defines events in the configurational energy landscape as a two-step process: (a) a configuration is first activated from a local minimum to a nearby saddle-point and (b) is then relaxed to a new minimum. Although ART has been applied with success to a wide range of materials such as a-Si, a-SiO2 and binary Lennard-Jones glasses, questions remain regarding the biases of the technique. We address some of these questions in a detailed study of ART-generated events in Lennard-Jones (LJ) clusters, a system for which much is already known. In particular, we study the distribution of saddle-points, the pathways between configurations, and the reversibility of paths. We find that ART can identify all trajectories with a first-order saddle point leaving a given minimum, is fully reversible, and samples events following the Boltzmann weight at the saddle point.Comment: 8 pages, 7 figures in postscrip

    Isomorph-free generation of 2-connected graphs with applications

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    Many interesting graph families contain only 2-connected graphs, which have ear decompositions. We develop a technique to generate families of unlabeled 2-connected graphs using ear augmentations and apply this technique to two problems. In the first application, we search for uniquely K_r-saturated graphs and find the list of uniquely K_4-saturated graphs on at most 12 vertices, supporting current conjectures for this problem. In the second application, we verifying the Edge Reconstruction Conjecture for all 2-connected graphs on at most 12 vertices. This technique can be easily extended to more problems concerning 2-connected graphs.Comment: 15 pages, 3 figures, 4 table
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