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.


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    Title :

    Comparative study on nature inspired algorithms for optimization problem


    Contributors:


    Publication date :

    2017-04-01


    Size :

    454607 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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