On global optimization in two-dimensional scaling

Authors

R. Mathar, A. Zilinskas,

Abstract

        We consider multidimensional scaling for embedding dimension two, which allows the detection of structures in dissimilarity data by simply drawing two dimensional figures. The corresponding objective function, called stress, in general is nondifferentiable and has many local minima. In this paper we investigate several features of this function, and discuss the application of different global optimization procedures. A method based on combining a local search algorithm with an evolutionary strategy of generating new initial points is proposed, and its efficiency is investigated by numerical examples.

BibTEX Reference Entry 

@article{MaZi93,
	author = {Rudolf Mathar and Antanas Zilinskas},
	title = "On global optimization in two-dimensional scaling",
	pages = "109-118",
	journal = "Acta Aplicandae Mathematicae",
	volume = "33",
	year = 1993,
	}

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