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- Title
ALGORITHMS WITH GREEDY HEURISTIC PROCEDURES FOR MIXTURE PROBABILITY DISTRIBUTION SEPARATION.
- Authors
KAZAKOVTSEV, Lev; STASHKOV, Dmitry; GUDYMA, Mikhail; KAZAKOVTSEV, Vladimir
- Abstract
For clustering problems based on the model of mixture probability distribution separation, we propose new Variable Neighbourhood Search algorithms (VNS) and evolutionary genetic algorithms (GA) with greedy agglomerative heuristic procedures and compare them with known algorithms. New genetic algorithms implement a global search strategy with the use of a special crossover operator based on greedy agglomerative heuristic procedures in combination with the EM algorithm (Expectation Maximization). In our new VNS algorithms, this combination is used for forming randomized neighbour-hoods to search for better solutions. The results of computational experiments made on classical data sets and the testings of production batches of semiconductor devices shipped for the space industry demonstrate that new algorithms allow us to obtain better results, higher values of the log likelihood objective function, in comparison with the EM algorithm and its modifications.
- Subjects
GREEDY algorithms; HEURISTIC algorithms; EXPECTATION-maximization algorithms; EVOLUTIONARY algorithms; SEARCH algorithms; MIXTURES
- Publication
Yugoslav Journal of Operations Research, 2019, Vol 29, Issue 1, p51
- ISSN
0354-0243
- Publication type
Article
- DOI
10.2298/YJOR171107030K