%0 Journal Article
%T Evolutionary Algorithms for Query Op-timization in Distributed Database Sys-tems: A review
%J -
%D 2018
%R http://dx.doi.org/10.14201/ADCAIJ201873115128
%X Evolutionary Algorithms are bio-inspired optimization problem-solving approaches that exploit principles of biological evolution. , such as natural selection and genetic inheritance. This review paper provides the application of evolutionary and swarms intelligence based query optimization strategies in Distributed Database Systems. The query optimization in a distributed environment is challenging task and hard problem. However, Evolutionary approaches are promising for the optimization problems. The problem of query optimization in a distributed database environment is one of the complex problems. There are several techniques which exist and are being used for query optimization in a distributed database. The intention of this research is to focus on how bio-inspired computational algorithms are used in a distributed database environment for query optimization. This paper provides working of bio-inspired computational algorithms in distributed database query optimization which includes genetic algorithms, ant colony algorithm, particle swarm optimization and Memetic Algorithms
%K Query optimization
%K Distributed data-base
%K Evolutionary Computation
%K Bio-inspired algorithms
%U http://campus.usal.es/~revistas_trabajo/index.php/2255-2863/article/view/ADCAIJ201873114128