Empirical evaluation of sequential, parallel and distributed implementations of k-means clustering [Elektronski vir]
Perkovič, Andreja ; Tošić, Aleksandar, 1989-
In this paper we present a sequential, parallel and distributed implementation of the infamous k-means clustering algorithm. We perform extensive testing of all three implementations on state the art ...hardware, and show the performance bene#ts of paralellization. The research was inspired by a use-case of reverse logistics optimisation of wood in Germany, which translates to a facility location problem. K-means is an heuristic approach that renders surprisingly good results compared to mathematical modelling approaches, which are usually not feasible in large inputs as they belong to the class of NP-hard problems.
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