Genetic Algorithm with Fast Greedy Heuristic for Clustering and Location Problems

Abstract

Authors propose new genetic algorithm for solving the planar p-median location problem and k-means clustering problem. The ideas of the algorithm are based on the genetic algorithm with greedy heuristic for the p-median problem on networks and information bottleneck (IB) clustering algorithms. The proposed algorithm uses the standard k-means procedure or any other similar algorithm for local search. The efficiency of the proposed algorithm in comparison with known algorithms was proved by experiments on large-scale location and clustering problems.

Authors

  • Lev A. Kazakovtsev
  • Alexander N. Antamoshkin

Downloads

How to Cite

Kazakovtsev, L. A., & Antamoshkin, A. N. (2014). Genetic Algorithm with Fast Greedy Heuristic for Clustering and Location Problems. Informatica, 38(3). Retrieved from https://www.informatica.si/index.php/informatica/article/view/704

Issue

Vol. 38 No. 3 (2014)

Section

Regular papers

License

Authors retain copyright in their work. By submitting to and publishing with Informatica, authors grant the publisher (Slovene Society Informatika) the non-exclusive right to publish, reproduce, and distribute the article and to identify itself as the original publisher.

All articles are published under the Creative Commons Attribution license CC BY 3.0. Under this license, others may share and adapt the work for any purpose, provided appropriate credit is given and changes (if any) are indicated.

Authors may deposit and share the submitted version, accepted manuscript, and published version, provided the original publication in Informatica is properly cited.