Ant colony optimization is an intelligent evolutionary algorithm that has been widely used in the field of path planning, and the research on its improved methods is proliferating. In this paper, the improvement methods of single and hybrid ant colony optimization in path planning are reviewed in terms of initial pheromone concentration, heuristic function, state transition rule, pheromone update rule, and parameter optimization, respectively. The future research directions of ant colony optimization have been prospected in terms of theoretical aspects, parameter setting and optimization, integration with other algorithms, and multiobjectives.


ant colony optimization; path planning; single ant colony optimization; hybrid ant colony optimization; improvement methods

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