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Integer Programming Methods for Seriation and Unidemensional Scaling of Proximity Matrices: A Review and Some Extensions

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L

1-norm are also presented. I conclude that the computational scaling problems depends largely on the criterion of interest, with unidimensional scaling problems depends largely on the criterion of interest, with unidimensional scaling in the L 1-norm being especially challenging.

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  1. Department of Marketing, College of Business, Florida State University, , , , ,

    Michael J. Brusco

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  1. Michael J. Brusco
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Brusco, M. Integer Programming Methods for Seriation and Unidemensional Scaling of Proximity Matrices: A Review and Some Extensions. J. of Classification 19, 45–67 (2002). https://doi.org/10.1007/s00357-001-0032-z

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  • DOI: https://doi.org/10.1007/s00357-001-0032-z

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