Journal of Research & Opinion peer-reviewed open access journal

Ant Colony Optimization Algorithms for Selection and Sequencing Problems

Sameh Shihabi
Industrial Engineering Department, The University of Jordan, Amman 1192, Jordan
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1.
Ant Colony Optimization Algorithms for Selection and Sequencing Problems. Journal of Research and Opinion [Internet]. 2021 Sep. 25 [cited 2024 Nov. 21];8(9):3019-22. Available from: https://researchopinion.in/index.php/jro/article/view/123
  • Articles
  • Submited: September 25, 2021
  • Published: September 25, 2021

Abstract

This paper is a simple tutorial for researchers interested in ant colony optimization (ACO) in general and max-min ant system (MMAS) in particular. The paper compares the differences in implementing these algorithms to solve sequencing and selection problems. For selection problems, we use the famous knapsack problem (KP) to demonstrate how MMAS can be used, wherease, for the sequencing problem, we use the famous travelling salesman problem (TSP). Results from the literature shows how a MMAS algorithm can outperform other meta-heuristics in solving these two types of problems.

References

[1] Dorigo, M., Birattari, M., &Stutzle, T. (2006). Ant colony optimization. IEEE computational intelligence magazine, 1(4), 28-39
https://doi.org/10.1109/MCI.2006.329691
[2] Agarwal, A., Lim, M. H., Er, M. J., & Chew, C. Y. (2005, August). ACO for a new TSP in region coverage. In 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems (pp. 1717-1722). IEEE.
https://doi.org/10.1109/IROS.2005.1545460
[3]Kong, M., Tian, P., & Kao, Y. (2008). A new ant colony optimization algorithm for the multidimensional knapsack problem. Computers & Operations Research, 35(8), 2672-2683.
https://doi.org/10.1016/j.cor.2006.12.029
[4] Al-Shihabi, S. (2004, September). Backtracking ant system for the traveling salesman problem. In International Workshop on Ant Colony Optimization and Swarm Intelligence (pp. 318-325). Springer, Berlin, Heidelberg.
Backtracking Ant System for the Traveling Salesman Problem | SpringerLink

[5] Al-Shihabi, S. (2004, August). Ants for Sampling in the Nested Partition Algorithm. In Hybrid Metaheuristics (pp. 11-18).
Al-Shihabi, S.: Ants for sampling in the nested partition... - Google Scholar

[6] Mandahawi, N., Al-Shihabi, S., &Altarazi, S. (2011). A max-min ant system to minimize total tardiness on a single machine with sequence dependent setup times implementing a limited budget local search. International Journal of Research and Reviews in Applied Sciences, 6(1), 30-40.
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[7] Al-Shihabi, S. (2016). A hybrid of max–min ant system and linear programming for the k-covering problem. Computers & Operations Research, 76, 1-11.
https://doi.org/10.1016/j.cor.2016.06.006

[8] Sammy Ibrahim (2021). Optimal holiday destination selection. International Journal of Advance Research, Ideas and Innovations in Technology, 7(5)
Optimal holiday destination selection (ijariit.com)

[9] Sammy Ibrahim (2021). Optimaltimeallocationinacademia-amax-minantsystem. International Research Journal of Modernization in Engineering Technology and Science, 3(9) fin_irjmets1631798401.pdf

[10] Stützle, T., & Hoos, H. H. (2000). MAX–MIN ant system. Future generation computer systems, 16(8), 889-914.https://doi.org/10.1016/S0167-739X(00)00043-1
How to Cite
1.
Ant Colony Optimization Algorithms for Selection and Sequencing Problems. Journal of Research and Opinion [Internet]. 2021 Sep. 25 [cited 2024 Nov. 21];8(9):3019-22. Available from: https://researchopinion.in/index.php/jro/article/view/123

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