Abstract: The scheduling problem model of distributed heterogeneous parallel machine is presented in the background of the actual production problems in industrial production. Then, a hybrid fruit fly optimization algorithm is designed to minimize the maximum completion time of the considered problem. Firstly, the competition mechanism is added in the initialization phase of the algorithm, which effectively improves the quality of the initial solution. Secondly, the adaptive search radius is introduced in the smell search stage to effectively search the solution space. Finally, the three-phase local search is integrated into the update phase of the algorithm, so global search and local search can achieve a better balance. Simulation experiments and algorithm comparisons verify the effectiveness and robustness of the proposed hybrid fruit fly optimization algorithm.

Key words: Distributed heterogeneous parallel machine, hybrid fruit fly optimization algorithm, competition mechanism, adaptive search radius

摘要： 以工业生产中面临的实际生产问题为背景，提出了分布式异构并行机的调度问题模型，进而针对该问题设计了一种混合果蝇优化算法，用于最小化最大完工时间。在算法中，首先，在初始化阶段加入竞争机制，有效地提高了初始解的质量；其次，在嗅觉搜索阶段引入了自适应搜索半径，实现了对解空间的有效搜索；最后，在更新阶段融入了三阶段局部搜索，使全局搜索和局部搜索达到了较好平衡。仿真实验和算法比较验证了所提混合果蝇优化算法的有效性和鲁棒性。

关键词: 分布式异构并行机, 混合果蝇优化算法, 竞争机制, 自适应的搜索半径