Bacterial foraging algorithm comes from the best survival selection mechanism of animals in nature. As the representative of the heuristic algorithm, the bacterial foraging algorithm has unique advantages in solving the multi difficulty scheduling problem effectively. In order to realize the artificial intelligent management of the enterprise’s staff scheduling, this paper constructs the knowledge staff scheduling model by using a bacterial foraging algorithm and analyzes the implementation principle, advantages, and disadvantages of the algorithm. The influence of the basic parameters in the algorithm model on the algorithm performance is analyzed. In order to optimize the unconventional foraging strategy, the improvement measures of bacterial foraging behavior were proposed. Finally, the performance of the optimized bacterial foraging algorithm is tested and compared with the basic bacterial foraging algorithm, genetic algorithm, and particle swarm optimization algorithm. The experimental results show that the optimized bacterial foraging algorithm can achieve better convergence accuracy and shorter convergence speed for the objective function, and it can solve the scheduling optimization problem of knowledge workers more quickly, accurately, and effectively. The research in this paper shows that the optimization of four aspects of the basic bacterial foraging algorithm improves the performance of the algorithm and provides a theoretical reference for the optimization of the bacterial foraging algorithm.

细菌觅食算法来源于自然界动物的最佳生存选择机制。作为启发式算法的代表，细菌觅食算法在有效解决多难度调度问题方面具有独特的优势。为实现企业员工排班的人工智能管理，本文利用细菌觅食算法构建了知识型员工排班模型，并分析了该算法的实现原理、优缺点。分析了算法模型中的基本参数对算法性能的影响。为了优化非常规觅食策略，提出了细菌觅食行为的改进措施。最后，对优化后的细菌觅食算法的性能进行了测试，并与基本细菌觅食算法、遗传算法和粒子群优化算法进行了性能对比。实验结果表明，优化后的细菌觅食算法对目标函数可以达到更好的收敛精度和更短的收敛速度，可以更快、更准确、更有效地解决知识工作者的调度优化问题。本文的研究表明，对基本细菌觅食算法的四个方面进行优化，提高了算法的性能，为细菌觅食算法的优化提供了理论参考。和粒子群优化算法。实验结果表明，优化后的细菌觅食算法对目标函数可以达到更好的收敛精度和更短的收敛速度，可以更快、更准确、更有效地解决知识工作者的调度优化问题。本文的研究表明，对基本细菌觅食算法的四个方面进行优化，提高了算法的性能，为细菌觅食算法的优化提供了理论参考。和粒子群优化算法。实验结果表明，优化后的细菌觅食算法对目标函数可以达到更好的收敛精度和更短的收敛速度，能够更快速、准确、有效地解决知识工作者的调度优化问题。本文的研究表明，对基本细菌觅食算法的四个方面进行优化，提高了算法的性能，为细菌觅食算法的优化提供了理论参考。准确、有效。本文的研究表明，对基本细菌觅食算法的四个方面进行优化，提高了算法的性能，为细菌觅食算法的优化提供了理论参考。准确、有效。本文的研究表明，对基本细菌觅食算法的四个方面进行优化，提高了算法的性能，为细菌觅食算法的优化提供了理论参考。