关键词: 零空闲流水线调度, 细菌觅食优化算法, NEH启发式算法, 自适应迁徙概率, 鲁棒性

Abstract: For No-Idle Flow shop Scheduling problem （NIFS） with the target of maximum makespan, a new solution named Improved Bacteria Foraging Optimization algorithm （IBFO） is proposed in this paper. Compared to BFO, 3 modifications are added in IBFO. In the chemotaxis process, it introduces a crossover operator. During the process of reproduction, it applies a hybrid strategy based on both health degree and target value of the bacterium. And for elimination process, it puts forward a self-adaption probability instead of a constant data. It tests IBFO through 6 different size Taillard problems by MATLAB, the results indicate that IBFO is feasible and effective. Further, in order to test the algorithm’s robustness to initial value, two methods are applied to get the initial bacterium population： random and NEH method.

Key words: No-Idle Flow shop Scheduling（NIFS）, Bacteria Foraging Optimization algorithm（BFO）, NEH heuristic algorithm, self-adaption migration probability, robustness