Abstract
The problem of multidimensional scaling with city-block distances in the embedding space is reduced to a two level optimization problem consisting of a combinatorial problem at the upper level and a quadratic programming problem at the lower level. A hybrid method is proposed combining randomized search for the upper level problem with a standard quadratic programming algorithm for the lower level problem. Several algorithms for the combinatorial problem have been tested and an evolutionary global search algorithm has been proved most suitable. An experimental code of the proposed hybrid multidimensional scaling algorithm is developed and tested using several test problems of two- and three-dimensional scaling.
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References
Arabie P (1991) Was Euclid an unnecessarily sophisticated psychologist?. Psychometrika 56: 567–587
Borg I, Groenen P (2005) Modern multidimensional scaling, 2nd edn. Springer, New York
Bortz J (1974) Kritische Bemerkungen über den Einsatz nicht-euklidischer Metriken im Rahmen der multidimensionalen Skalierung. Archiv für Psychologie 126: 196–212
Brusco MJ (2001) A simulated annealing heuristics for unidimensional and multidimensional (city block) scaling of symmetric proximity matrices. J Classif 18: 3–33
Cox T, Cox M (2001) Multidimensional scaling. Chapman & Hall/CRC, London/Boca Raton
de Leeuw J (1984) Differentiability of Kruskal’s stress at a local minimum. Psychometrika 49: 111–113
Everett JE (2001) Algorithms for multidimensional scaling. In: Chambers LD(eds) The practical handbook of genetic algorithms, 2nd edn. Chapman & Hall/CRC, London/Boca Raton, pp 203–233
Green P, Carmone F, Smith S (1989) Multidimensional scaling: concepts and applications. Allyn and Bacon, Boston
Groenen PJF, Heiser WJ, Meulman JJ (1998) City-block scaling: smoothing strategies for avoiding local minima. In: Balderjahn I, Mathar R, Schader M(eds) Classification, data analysis, and data highways. Springer, Heidelberg, pp 46–53
Groenen PJF, Heiser WJ, Meulman JJ (1999) Global optimization in least-squares multidimensional scaling by distance smoothing. J Classif 16: 225–254
Groenen PJF, Mathar R, Heiser WJ (1995) The majorization approach to multidimensional scaling for Minkowski distances. J Classif 12: 3–19
Groenen P, Mathar R, Trejos J (2000) Global optimization methods for multidimensional scaling applied to mobile communication. In: Gaul W, Opitz O, Schander M(eds) Data analysis: scientific modeling and practical applications. Springer, Heidelberg, pp 459–475
Hooker JN (1995) Testing heuristics: we have it all wrong. J Heuristics 1: 33–42
Hubert L, Arabie P, Hesson-Mcinnis M (1992) Multidimensional scaling in the city-block metric: a combinatorial approach. J Classif 9: 211–236
Hubert L, Arabie P, Meulman J (2006) The structural representation of proximity matrices with Matlab. SIAM, Philadelphia
Leung PL, Lau K (2004) Estimating the city-block two-dimensional scaling model with simulated annealing. Eur J Oper Res 158: 518–524
Mathar R, Žilinskas A (1993) On global optimization in two-dimensional scaling. Acta Appl Math 33: 109–118
Michalewicz Z (1996) Genetic algorithms + data structures = evolution programs. Springer, Berlin
Murillo A, Vera JF, Heiser WJ (2005) A permutation-translation simulated annealing algorithm for L1 and L2 unidimensional scaling. J Classif 22: 119–138
TTörn A, Žilinskas A (1989) Global optimization. Lect Notes Comput Sci 350: 1–250
Žilinskas A, Žilinskas J (2006) Parallel hybrid algorithm for global optimization of problems occurring in MDS-based visualization. Comput Math Appl 52: 211–224
Žilinskas A, Žilinskas J (2007) Two level minimization in multidimensional scaling. J Global Optim 38: 581–596
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Žilinskas, A., Žilinskas, J. A hybrid method for multidimensional scaling using city-block distances. Math Meth Oper Res 68, 429–443 (2008). https://doi.org/10.1007/s00186-008-0238-5
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DOI: https://doi.org/10.1007/s00186-008-0238-5