ABCO: Adaptive Bacterial Colony Optimisation
Abstract
This paper introduces a new optimisation algorithm, called Adaptive Bacterial Colony Optimisation (ABCO), modelled after the foraging behaviour of E. coli bacteria. The algorithm follows three stages--explore, exploit and reproduce--and is adaptable to meet the requirements of its applications. The performance of the proposed ABCO algorithm is compared to that of established optimisation algorithms--particle swarm optimisation (PSO) and ant colony optimisation (ACO)--on a set of benchmark functions. Experimental results demonstrate the benefits of the adaptive nature of the proposed algorithm: ABCO runs much faster than PSO and ACO while producing competitive results and outperforms PSO and ACO in a scenario where the running time is not crucial.
Cite
@article{arxiv.2505.01320,
title = {ABCO: Adaptive Bacterial Colony Optimisation},
author = {Barisi Kogam and Yevgeniya Kovalchuk and Mohamed Medhat Gaber},
journal= {arXiv preprint arXiv:2505.01320},
year = {2025}
}