Joint stocker placement and scheduling in automated material handling-enabled reentrant hybrid flow shops
研究了自动化物料搬运环境下可重入混合流水车间中料架布局与调度的联合优化问题，提出改进混合猴搜索算法，发现将料架布置在首入站前一个阶段能显著缩短完工时间，对高利用率和大规模场景尤其有效。
Automated material handling systems (AMHS) in reentrant hybrid flow shops (RHFS) are widely used in high-value manufacturing, where jobs revisit processing stages for rework or inspection, increasing the risk of work-in-progress (WIP) congestion. Existing studies commonly mitigate this issue using machine buffers and stockers but typically assume a one-to-one correspondence between stations and stockers, despite industrial evidence indicating that fewer stockers may suffice. Moreover, heterogeneity in station utilisation suggests that stocker placement decisions can critically affect system performance, yet this aspect remains underexplored. This study investigates a joint stocker placement and scheduling problem for AMHS-enabled RHFS, explicitly considering reduced stocker availability and flexible allocation across stations. The problem integrates structural resource configuration with operational scheduling decisions and is shown to be NP-hard. An improved hybrid monkey search algorithm is developed to efficiently solve the integrated problem. Computational experiments demonstrate that coordinated stocker placement and scheduling significantly reduce makespan compared with conventional uniform allocation assumptions. The results further reveal that placing stockers at stations one stage ahead of first-entry stations yields notable performance improvements, particularly under high utilisation and large-scale settings. These findings provide practical insights for configuring temporary storage resources in reentrant production systems.