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The application of the improved Ant Colony Algorithm in mine locomotive scheduling problem

机译:改进的蚁群算法在矿井机车调度问题中的应用

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Ant Colony Algorithm has some advantages in solving complex optimization problems, in particular discrete optimization problem. A mine locomotive scheduling algorithm based on the improved Ant Colony Algorithm for the mine locomotive scheduling problem has proposed in this paper. The method takes simulated annealing algorithm as a local search strategy of ant colony algorithm, aim at expanding the solution search space, avoiding falling into local optimum that improve convergence rate of the algorithm by dynamic pheromone evaporation factor. Simulation results show that the algorithm is more efficiency in locomotive scheduling than the basic ant colony algorithm.
机译:蚁群算法在解决复杂优化问题方面具有一些优点,特别是离散优化问题。本文提出了一种基于矿井机车调度问题改进蚁群算法的矿井机车调度算法。该方法采用模拟退火算法作为蚁群算法的本地搜索策略,旨在扩展解决方案搜索空间,避免落入局部最佳,通过动态信息素蒸发因子提高算法的收敛速率。仿真结果表明,该算法比基本蚁群算法更高的机车调度效率。

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