Authors V.B. Lebedev
Month, Year 06, 2014 @en
Index UDC 004.62
Abstract In this paper we present the problem of the formation of a distributed database based on the set of local databases. Solved the problem of choosing the configuration and determine the composition of library collections each local database In this regard, there is the task of covering the content distributed data storage minimum set of local databases. The considered problem is equivalent to the set covering and is NP-complete. For a compact representation of the solution of the covering problem using a matrix boundary requirements. In this paper we present a method of solving the problem of coverage based on swarm intelligence. Used compact symbolic representation of the solution of the covering problem. It is possible to organize the space of solutions using unordered linguistic scale in which organized search process based on simulation of adaptive behavior of particle swarm. The paper proposes an approach to constructing a hybrid structure of finding a solution based on a combination of genetic search methods swarm intelligence. The developed algorithm cover are universal and can be used for a wide range of linear integer programming. Compared with existing algorithms to improve the results achieved.

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Keywords Distributed database; the local database; data warehouse; coating; adaptive behavior; particle swarm; optimization.
References 1. Деньдобренко Б.П., Малика А.С. Автоматизация проектирования радиоэлектронной аппаратуры. – М.: Высш. шк., 2002.
2. Coudert O. “On solving covering problems”, in proceedings of 30th ACM // IEEE Design automation conference. – 1996. – P. 197-202.
3. Cordone R., Ferrandi F., Sciuto D., Calvo R.W. An Efficient Heuristic Approach to Solve the Unate Covering Problem // IEEE Transactions on computer-aided design of integrated circuits and systems. – December 2001. – Vol. 120, № 12. – P. 1377-1387.
4. Лебедев О.Б. Покрытие методом муравьиной колонии // Двенадцатая национальная конференция по искусственному интеллекту с международным участием КИИ-2010. Труды конференции. Т. 2. – М.: Физматлит, 2010. – С. 423-431.
5. Курейчик В.М., Лебедев Б.К., Лебедев О.Б. Поисковая адаптация: теория и практика. – М.: Физматлит, 2006.
6. Курейчик В.М., Лебедев Б.К., Лебедев О.Б. Решение задачи покрытия на основе эволюционного моделирования // Теория и системы управления. – 2009. – № 1. – С. 101-116.
7. Лебедев Б.К., Лебедев В.Б. Размещение на основе метода пчелиной колонии // Известия ЮФУ. Технические науки. – 2010. – № 12 (113). – С. 12-19.
8. Лебедев Б.К., Лебедев О.Б. Моделирование адаптивного поведения муравьиной колонии при поиске решений, интерпретируемых деревьями // Известия ЮФУ. Технические науки. – 2012. – № 7 (132). – С. 27-34.
9. Poli R. Analysis of the publications on the applications of particle swarm optimization // Journal of Artificial Evolution and Applications, Article ID 685175. – 2008. – P. 10.
10. Clerc M. Particle Swarm Optimization. ISTE, London, UK, 2006.

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