In this paper, a self-adaptive differential evolution (DE) algorithm is designed to solve multi-objective flow shop scheduling problems with limited buffers (FSSPwLB). The makespan and the largest job delay are treated as two separate objectives which are optimized simultaneously. To improve the performance of the proposed algorithm and eliminate the difficulty of setting parameters, an adaptive mechanism is designed and incorporated into DE. Moreover, various local search and hybrid meta-heuristic methods are presented and compared to improve the convergence. Through the analysis of the experimental results, the proposed algorithm is able to tackle the FSSPwLB problems effectively by generating superior and stable scheduling strategies.

中文翻译：

---

使用混合自适应差分进化的有限缓冲区多目标流水车间调度

本文设计了一种自适应差分进化算法（DE）来解决有限缓冲区的多目标流水车间调度问题（FSSPwLB）。工期和最大的工作延迟被视为同时优化的两个独立目标。为了提高所提出算法的性能并消除参数设置的难度，设计了一种自适应机制并将其结合到DE中。此外，提出并比较了各种局部搜索和混合元启发式方法，以提高收敛性。通过对实验结果的分析，提出的算法能够通过生成更好的，稳定的调度策略来有效解决FSSPwLB问题。