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Zulfiqar Ali
The University of Lahore, Lahore, Pakistan.
Hafiza Maria Kiran
The University of Lahore, Lahore.
Waseem Shahzad
National University of Computer and Emerging Sciences
Vol. 7 No. 3 (2018), Articles, pages 115-128
Accepted: Sep 24, 2018


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.


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