Dorigo, M., Maniezzo, V., & Colorni, A. (1996). The Ant System:
Optimization by a colony of cooperating agents. IEEE Transactions on
Systems, Man, and Cybernetics. Part B: Cybernetics, 26(1), 29-41.
doi:10.1109/3477.484436
Dorigo, M., Birattari, M., & Stützle, T. (2006). Ant colony optimization:
Artificial ants as a computational intelligence technique. IEEE
Computational Intelligence Magazine, 1(4), 28-39.
doi:10.1109/MCI.2006.329691
Socha, K., & Dorigo, M. (2008). Ant colony optimization for continuous
domains. European Journal of Operational Research, 185(3), 1155-1173.
doi:10.1016/j.ejor.2006.06.046
Socha, K. (2007). Ant colony optimization for continuous and mixed-variable
domains [Doctoral dissertation, Université Libre de Bruxelles]. IRIDIA.
Deneubourg, J.-L., Aron, S., Goss, S., & Pasteels, J. M. (1990). The
self-organizing exploratory pattern of the Argentine ant. Journal of Insect
Behavior, 3, 159-168.
doi:10.1007/BF01417909
Ezugwu, A. E., Adeleke, O. J., Akinyelu, A. A., & Viriri, S. (2020). A
conceptual comparison of several metaheuristic algorithms on continuous
optimisation problems. Neural Computing and Applications, 32, 6207-6251.
doi:10.1007/s00521-019-04132-w
Game, P. S., Vaze, V., & Emmanuel, M. (2020). Bio-inspired optimization:
Metaheuristic algorithms for optimization. arXiv:2003.11637.
doi:10.48550/arXiv.2003.11637
Induraj. “Implementing Ant Colony Optimization in Python - solving Traveling
Salesman Problem.”
link
Movable Type Scripts. “Calculate distance, bearing and more between
Latitude/Longitude points.”
link