Multi-manned assembly line, which is broadly utilized to assemble high volume products such as automobiles and trucks, allows a group of workers to assemble different tasks simultaneously in a multi-manned workstation. This additional characteristic of parallel operators increases the complexity of the traditional NP-hard assembly line balancing problem. Hence, this paper formulates the Type-I multi-manned assembly line balancing problem to minimize the total number of workstations and operators, and develops an efficient migrating birds optimization algorithm embedded into an idle time reduction method. In this algorithm, a new decoding mechanism is proposed which reduces the sequence-dependent idle time by some task assignment rules; three effective neighborhoods are developed to make refinement of existing solutions in the bird improvement phases; and temperature acceptance and competitive mechanism are employed to avoid being trapped in the local optimum. Comparison experiments suggest that the new decoding and improvements are effective and the proposed algorithm outperforms the compared algorithms.

中文翻译：

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一种有效的减少闲置时间的迁鸟优化算法，用于I型多人流水线平衡问题

多人装配线被广泛用于装配大批量产品，例如汽车和卡车，它使一群工人可以在多人工作站中同时装配不同的任务。并行运算符的这一附加特性增加了传统NP硬装配线平衡问题的复杂性。因此，本文提出了I型多人流水线平衡问题，以最大程度地减少工作站和操作员的总数，并开发了一种嵌入空闲时间减少方法的有效迁鸟优化算法。该算法提出了一种新的解码机制，该机制可以通过一些任务分配规则来减少与序列相关的空闲时间。开发了三个有效的社区，以完善鸟类改良阶段的现有解决方案；并采用温度接受和竞争机制来避免陷入局部最优状态。比较实验表明，新的解码和改进是有效的，并且所提出的算法优于所比较的算法。