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Parallel branch and bound for multidimensional scaling with city-block distances

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  • Julius Žilinskas

Abstract

Multidimensional scaling is a technique for exploratory analysis of multidimensional data. The essential part of the technique is minimization of a multimodal function with unfavorable properties like invariants and non-differentiability. Recently a branch and bound algorithm for multidimensional scaling with city-block distances has been proposed for solution of medium-size problems exactly. The algorithm exploits piecewise quadratic structure of the objective function. In this paper a parallel version of the branch and bound algorithm for multidimensional scaling with city-block distances has been proposed and investigated. Parallel computing enabled solution of larger problems what was not feasible with the sequential version. Copyright Springer Science+Business Media, LLC. 2012

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  • Julius Žilinskas, 2012. "Parallel branch and bound for multidimensional scaling with city-block distances," Journal of Global Optimization, Springer, vol. 54(2), pages 261-274, October.
    • Handle: RePEc:spr:jglopt:v:54:y:2012:i:2:p:261-274
    DOI: 10.1007/s10898-010-9624-7
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    References listed on IDEAS

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