Тип публикации: доклад, тезисы доклада, статья из сборника материалов конференций
Год издания: 2016
Идентификатор DOI: 10.1088/1757-899X/122/1/012011
Ключевые слова: Algorithms, Genetic algorithms, Heuristic algorithms, Problem solving, Algorithm for solving, Clustering problems, Computational experiment, Greedy heuristics, Number of clusters, P-median, Production batches, SPACE system, Clustering algorithms
Аннотация: Algorithms based on using the agglomerative greedy heuristics demonstrate precise and stable results for clustering problems based on k- means and p-median models. Such algorithms are successfully implemented in the processes of production of specialized EEE components for using in space systems which include testing each EEE devicПоказать полностьюe and detection of homogeneous production batches of the EEE components based on results of the tests using p-median models. In this paper, authors propose a new version of the genetic algorithm with the greedy agglomerative heuristic which allows solving series of problems. Such algorithm is useful for solving the k-means and p-median clustering problems when the number of clusters is unknown. Computational experiments on real data show that the preciseness of the result decreases insignificantly in comparison with the initial genetic algorithm for solving a single problem. © Published under licence by IOP Publishing Ltd.
Журнал: IOP Conference Series: Materials Science and Engineering
Выпуск журнала: Vol. 122, Is. 1