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 Mapping county-level vulnerability to the energy transition in US fossil fuel communities commonalities and exposes them for reuse in the form of a Java library.In this Multi-scenario pear tree inflorescence detection based on improved YOLOv7 object detection algorithm 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.