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2024 International Conference on Information Technologies

Search Algorithms with Randomized Variable Neighborhoods for Solving Series of Clustering Problems

Ilnar Nasyrov
Mikhail Gudyma
Lev Kazakovtsev
Dmitry Stashkov
Reshetnev Siberian State University of Science and Technology
Siberian Federal University
JSC "SINETIC"
Russian Federation
e-mail: levk@bk.ru
Abstract:

In this paper, we propose new algorithms for solving the classical problem of cluster analysis, k-Means, which uses the variable neighbourhoods search in randomized neighbourhoods formed by running the greedy agglomerative procedures. A comparison with known algorithms including the algorithms with greedy heuristics is given, and the advantage is confirmed experimentally.

Key words:
clustering genetic algorithm
greedy agglomerative heuristic
k-means
p-median