%0 Journal Article
%T A Heuristic Search Approach to Multidimensional Scaling
%A Patrick R. McMullen
%J American Journal of Operations Research
%P 179-193
%@ 2160-8849
%D 2022
%I Scientific Research Publishing
%R 10.4236/ajor.2022.125010
%X This
research effort presents an approach to accomplish Multidimensional Scaling
(MDS) via the heuristic approach of Simulated Annealing. Multidimensional
scaling is an approach used to convert matrix-based similarity (or
dissimilarity data) into spatial form, usually via two or three dimensions.
Performing MDS has several important applications</span></span><span><span><span style=\"font-family:&quot;\">¡ª<span>Geographic Information Systems, DNA
Sequencing, and Marketing Research are just a few. Traditionally, classical MDS
decomposes the similarity or dissimilarity matrix into its eigensystem and uses
the eigensystem to calculate spatial coordinates. Here, a heuristic
search-based approach is used to find coordinates from a dissimilarity matrix
that minimizes a cost function. The proposed methodology is used over a variety
of problems. Experimentation shows that the presented methodology consistently
outperforms solutions obtained via the classical MDS approach, and this
approach can be used for other important applications.
%K Optimization
%K Search
%K Heuristic
%U http://www.scirp.org/journal/PaperInformation.aspx?PaperID=119806