Genetic Algorithm with Fast Greedy Heuristic for Clustering and Location Problems

Authors

  • Lev A. Kazakovtsev
  • Alexander N. Antamoshkin

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.

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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://puffbird.ijs.si/index.php/informatica/article/view/704

Issue

Vol. 38 No. 3 (2014)

Section

Regular papers

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