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

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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.

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  1. Institute of Mathematics and Informatics, Vilnius University, Akademijos 4, 08663, Vilnius, Lithuania

    Julius Žilinskas

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  1. Julius Žilinskas
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Žilinskas, J. Parallel branch and bound for multidimensional scaling with city-block distances. J Glob Optim 54, 261–274 (2012). https://doi.org/10.1007/s10898-010-9624-7

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  • DOI: https://doi.org/10.1007/s10898-010-9624-7

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