Isula: A java framework for ant colony algorithms | Zendy

Carlos Gavidia-Calderon | Zendy; César Beltrán | Zendy

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Isula: A java framework for ant colony algorithms

Author(s) -

Carlos Gavidia-Calderon,

César Beltrán

Publication year - 2020

Publication title -

softwarex

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.528

H-Index - 21

ISSN - 2352-7110

DOI - 10.1016/j.softx.2020.100400

Subject(s) - java , computer science , ant colony optimization algorithms , reuse , travelling salesman problem , ant colony , segmentation , algorithm , artificial intelligence , operating system , ecology , biology

Ant Colony Optimisation (ACO) algorithms emulate the foraging behaviour of ants to solve optimisation problems. They have proven effective in both academic and industrial settings. ACO algorithms share many features among them. Isula encapsulates these commonalities and exposes them for reuse in the form of a Java library. In this paper, we use the travelling salesman problem and image segmentation to showcase the framework capabilities using three top-performing ACO algorithms implemented in Isula. This framework is an open-source project available at GitHub, where is currently the most popular ACO java repository.

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