Lev Kazakovtsev

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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(More)
Genetic algorithm with greedy heuristic is an efficient method for solving largescale location problems on networks. In addition, it can be adapted for solving continuous problems such as k-means. In this article, authors propose modifications to versions of this algorithm on both networks and continuous space improving its performance. The Probability(More)
In this paper, we consider an approach to developing parallel versions of the algorithms based on the modified probability changing method for constrained pseudo-Boolean optimization. Optimization algorithms are adapted for the systems with shared memory (OpenMP) and cluster systems (MPI). The parallel efficiency is estimated for the large-scale non-linear(More)
The multi-facility Weber location problem is transformed into a pseudo-Boolean optimization problem and solved with use of a heuristic random search anytime-algorithm. Fermat-Weber problem in its simplest form (unconstrained, single facility, Euclidean metric) is well investigated. A lot of algorithms are developed for more complex cases. However, the(More)
Continuous location models are the oldest models in locations analysis dealing with the geometrical representations of reality, and they are based on the continuity of location area. The classical model in this area is the Weber problem. Distances in the Weber problem are often taken to be Euclidean distances, but almost all kinds of the distance functions(More)
In this paper, we investigate application of various options of algorithms with greedy agglomerative heuristic procedure for object clustering problems in continuous space in combination with various local search methods. We propose new modifications of the greedy agglomerative heuristic algorithms with local search in SWAP neighborhood for the p-medoid(More)