Journal of System Simulation
Abstract
Abstract: The traditional ant colony algorithm has many problems in convergence and diversity when solving the traveling salesman problem (TSP). Therefore, this paper proposes a heterogeneous multi-ant colony algorithm that combines the competitive interaction strategy and the eliminating-reconstructing mechanism (CEACO) to overcome these shortcomings. Firstly, the algorithm uses a competitive interaction strategy, which adjusts the interaction period adaptively according to the Hamming distance of different groups in different periods. Competition coefficients are adopted to differentiate matching interaction objects for interaction. The matched objects interact with each other through the optimal solution and pheromone matrix. This mechanism achieves a balance between algorithm convergence speed and diversity. Secondly, the algorithm uses the eliminating-reconstructing mechanism, which periodically eliminates and reconstructs the poor-searching populations to improve the solution accuracy of the algorithm.Finally, several groups of simulation experiments prove that the algorithm outperforms other methods in improving the solution accuracy and convergence speed.
Recommended Citation
Feng, Chen; You, Xiaoming; and Liu, Sheng
(2024)
"Heterogeneous Multi-ant Colony Algorithm Combining Competitive Interaction Strategy and Eliminatingreconstructing
Mechanism,"
Journal of System Simulation: Vol. 36:
Iss.
1, Article 18.
DOI: 10.16182/j.issn1004731x.joss.22-1009
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol36/iss1/18
First Page
232
Last Page
248
CLC
TP18
Recommended Citation
Feng Chen, You Xiaoming, Liu Sheng. Heterogeneous Multi-ant Colony Algorithm Combining Competitive Interaction Strategy and Eliminating-reconstructing Mechanism[J]. Journal of System Simulation, 2024, 36 (1): 232-248.
DOI
10.16182/j.issn1004731x.joss.22-1009
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