TY - JOUR
T1 - Isula
T2 - A java framework for ant colony algorithms
AU - Gavidia-Calderon, Carlos
AU - Beltrán Castañon, César
N1 - Publisher Copyright:
© 2020 The Authors
PY - 2020/1/1
Y1 - 2020/1/1
N2 - 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.
AB - 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.
KW - Ant colony optimisation
KW - Image segmentation
KW - Java
KW - Travelling salesman problem
UR - http://www.scopus.com/inward/record.url?scp=85078027956&partnerID=8YFLogxK
U2 - 10.1016/j.softx.2020.100400
DO - 10.1016/j.softx.2020.100400
M3 - Article
AN - SCOPUS:85078027956
SN - 2352-7110
VL - 11
JO - SoftwareX
JF - SoftwareX
M1 - 100400
ER -