Turkensteen, Marcel5; Andersen, Kim Allan5; Bang-Jensen, Jørgen4
1 CORAL - Centre for Operations Research Applications in Logistics, Aarhus School of Business, Aarhus BSS, Aarhus University2 Department of Business Studies, Aarhus School of Business, Aarhus BSS, Aarhus University3 Department of Economics and Business Economics, Aarhus BSS, Aarhus University4 unknown5 Department of Economics and Business Economics, Aarhus BSS, Aarhus University
In Clustering Problems, groups of similar subjects are to be retrieved from data sets. In this paper, Clustering Problems with the frequently used Minimum Sum-of-Squares Criterion are solved using meta-heuristic search. Tabu search has proved to be a successful methodology for solving optimization problems, but applications to large clustering problems are rare. The simulated annealing heuristic has mainly been applied to relatively small instances. In this paper, we implement tabu search and simulated annealing approaches and compare them to the commonly used k-means approach. We find that the meta-heuristic search methods are able to return solutions of very high quality.
Main Research Area:
MIC 2009 - VIII Metaheuristic International Conference