Just-in-time production in large enterprises along with the factory’s limited space highlights the need for scheduling tools that consider blocking conditions. This study contributes to the scheduling literature by developing an effective metaheuristic to address the Blocking Flowshop Scheduling Problems with Sequence-Dependent Setup-Times (BFSP with SDSTs). Including a new constructive heuristic and a local search mechanism customized for the blocking and setup time features, the Extended Iterated Greedy (EIG) algorithm effectively solves this highly intractable scheduling extension. The performance of the EIG algorithm is compared with that of the best-performing algorithms in the literature developed to solve the BFSP with SDSTs. Extensive numerical tests and statistical analyses verify EIG’s superiority over the benchmark algorithms and show that EIG performs steadily over various operational situations. Applications of the improved algorithm in this study are worthwhile topics to solve other complex scheduling problems.

大型企业中的即时生产以及工厂有限的空间凸显了对考虑阻塞条件的调度工具的需求。这项研究通过开发一种有效的元启发式方法，以解决序列依赖的建立时间（带有SDST的BFSP）的阻塞Flowshop调度问题，为调度文献做出了贡献。扩展的迭代贪婪（EIG）算法包括针对阻塞和建立时间功能而定制的新的构造试探法和本地搜索机制，可以有效地解决这一难以解决的调度扩展问题。将EIG算法的性能与文献中为解决带有SDST的BFSP而开发的最佳算法的性能进行了比较。大量的数值测试和统计分析证明了EIG在基准算法上的优越性，并表明EIG在各种运行情况下均能稳定运行。改进算法在本研究中的应用是解决其他复杂调度问题的主题。