Nature inspired algorithms are gaining popularity for optimizing complex problems. These algorithms have been classified into 2 general categories, namely Evolutionary and Swarm Intelligence, which have further been divided into a couple of algorithms. This paper presents a comparative study between Bat Algorithm, Genetic algorithm, Artificial Bee Colony Algorithm and Ant Colony Optimization Algorithm. These algorithms are compared on the basis of various factors such as Efficiency, Accuracy, Performance, Reliability and Computation Time. At the end, a table has been created which enables the reader to easily differentiate between them and realise which algorithm outperforms the others.
Comparative study on nature inspired algorithms for optimization problem
2017-04-01
454607 byte
Conference paper
Electronic Resource
English
Nature Inspired Optimization Methods
DataCite | 2018
|Nature Inspired Optimization Methods, Vorlesung, SS 2017
DataCite | 2017
|Nature Inspired Optimization Methods, SS 2018, 07.05.2018
DataCite | 2018
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