In this article, we present an improved hybrid algorithm based on ant colony optimization and the polycephalum algorithm. First, we use improved the probability selection mechanism in the ant colony algorithm in order to improve the efficiency of next point searching. Second, in each iteration we update the pheromone concentration of the optimal route by using the polycephalum algorithm. We regard the starting point of the optimal route as the water injection point and the end point as the water outlet point. The hybrid algorithm is compared on multiple TSPLIB problems and flexible job shop scheduling problems. And experiments show that the improved algorithm has good application results and resultful in accuracy and optimal solutions.

中文翻译：

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混合集群算法在柔性作业车间调度问题中的应用

在本文中，我们提出了一种基于蚁群优化和多头算法的改进混合算法。首先，我们在蚁群算法中使用改进的概率选择机制，以提高下一个点搜索的效率。其次，在每次迭代中，我们通过使用 polycephalum 算法更新最佳路线的信息素浓度。我们以最优路线的起点为注水点，终点为出水点。混合算法在多个 TSPLIB 问题和灵活的作业车间调度问题上进行了比较。实验表明，改进后的算法具有良好的应用效果，得到了准确的解和最优解。