Artificial Bee Colony with Crossover Operations for Discrete Problems


  • A. H. Alaidi Programming Department, Computer Science and Information Technology College, Wasit University, Iraq
  • S. D. Chen College of Computing and Informatics, Universiti Tenaga Nasional, Malaysia
  • Υ. Weng Leong College of Engineering, Universiti Tenaga Nasional, Malaysia
Volume: 12 | Issue: 6 | Pages: 9510-9514 | December 2022 |


The Artificial Bee Colony (ABC) is an algorithm designed to solve continuous problems. ABC has been proven to be more effective than other biological-inspired algorithms. However, it is needed to modify its functionality in order to solve a discrete problem. In this work, a natural modification to the original ABC is made to make it able to solve discrete problems. Six neighborhood operators are proposed to simulate the original behavior of ABC. Moreover, several Traveling Salesman Problem Library (TSPLIB) problems were used to examine the proposed method. The results of the proposed method are promising.


TSP, Artificial Bee Colony, discrete problem


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Q. Gu, Q. Wang, X. Li, and X. Li, "A surrogate-assisted multi-objective particle swarm optimization of expensive constrained combinatorial optimization problems," Knowledge-Based Systems, vol. 223, Jul. 2021, Art. No. 107049. DOI:

Ι. Marouani, A. Boudjemline, T. Guesmi, and H. H. Abdallah, "A Modified Artificial Bee Colony for the Non-Smooth Dynamic Economic/Environmental Dispatch," Engineering, Technology & Applied Science Research, vol. 8, no. 5, pp. 3321–3328, Oct. 2018. DOI:

S. D. Chavan and A. V. Kulkarni, "Event Based Clustering Localized Energy Efficient Ant Colony Optimization (EBC_LEE-ACO) for Performance Enhancement of Wireless Sensor Network," Engineering, Technology & Applied Science Research, vol. 8, no. 4, pp. 3177–3183, Aug. 2018. DOI:

H. Ehteshami, S. Javadi, and S. M. Shariatmadar, "Improving the Power Quality in Tehran Metro Line-Two Using the Ant Colony Algorithm," Engineering, Technology & Applied Science Research, vol. 7, no. 6, pp. 2256–2259, Dec. 2017. DOI:

D. Karaboga and B. Akay, "A modified Artificial Bee Colony (ABC) algorithm for constrained optimization problems," Applied Soft Computing, vol. 11, no. 3, pp. 3021–3031, Apr. 2011. DOI:

M. M. Nasiri, "A modified ABC algorithm for the stage shop scheduling problem," Applied Soft Computing, vol. 28, pp. 81–89, Mar. 2015. DOI:

M. S. Kıran, H. İşcan, and M. Gündüz, "The analysis of discrete artificial bee colony algorithm with neighborhood operator on traveling salesman problem," Neural Computing and Applications, vol. 23, no. 1, pp. 9–21, Jul. 2013. DOI:

D. B. Fogel, "An evolutionary approach to the traveling salesman problem," Biological Cybernetics, vol. 60, no. 2, pp. 139–144, Dec. 1988. DOI:

J. McCaffrey, "Test Run - Ant Colony Optimization," MSDN Magazine Issues, vol. 27, no. 2, Feb. 2016, [Online]. Available:

G. Reinelt, "TSPLIB—A Traveling Salesman Problem Library," ORSA Journal on Computing, vol. 3, no. 4, pp. 376–384, Nov. 1991. DOI:

D. Karaboga and B. Basturk, "A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm," Journal of Global Optimization, vol. 39, no. 3, pp. 459–471, Oct. 2007. DOI:

S. ArunKumar, B. V. Kumar, and M. Pandi, "Artificial bee colony optimization based energy-efficient wireless network interface selection for industrial mobile devices," Computer Communications, vol. 154, pp. 1–10, Mar. 2020. DOI:

H. Gao, Z. Fu, C.-M. Pun, J. Zhang, and S. Kwong, "An Efficient Artificial Bee Colony Algorithm With an Improved Linkage Identification Method," IEEE Transactions on Cybernetics, vol. 52, no. 6, pp. 4400–4414, Jun. 2022. DOI:

S. S. Choong, L.-P. Wong, and C. P. Lim, "An artificial bee colony algorithm with a Modified Choice Function for the traveling salesman problem," Swarm and Evolutionary Computation, vol. 44, pp. 622–635, Feb. 2019. DOI:


How to Cite

A. H. Alaidi, S. D. Chen, and Weng Leong Υ., “Artificial Bee Colony with Crossover Operations for Discrete Problems”, Eng. Technol. Appl. Sci. Res., vol. 12, no. 6, pp. 9510–9514, Dec. 2022.


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