Make-to-availability (MTA) is a subtype of make-to-stock that emerged from production, planning, and control system, simplified drum-buffer-rope (S-DBR). The dispatching production order logic of the MTA does not consider the elements present in a wide range of manufacturing systems, such as sequence-dependent setup time. These characteristics generally creates difficulties in the S-DBR, thereby worsening performance indicators, such as mean flow time, setup time, and stock replenishment frequency. Given this research gap, the present study aims to develop a dispatching method for production orders in MTA, based on the particle swarm optimization (PSO) metaheuristic. The dispatching method aims to minimize the mean flow time, setup time, and stock levels in environments with a dependent setup time. To evaluate the performance of the new dispatching method, we used computational simulation to compare this method and the MTA dispatching logic. The results showed that the PSO for sequence achieved better performance, reducing the mean flow time, setup time, and stock level.

按库存生产（MTA）是按库存生产的一种子类型，它是从生产，计划和控制系统简化的桶式缓冲绳（S-DBR）中产生的。MTA的分派生产订单逻辑不考虑各种制造系统中存在的元素，例如与序列有关的建立时间。这些特性通常会在S-DBR中造成困难，从而使性能指标恶化，例如平均流动时间，建立时间和库存补充频率。鉴于此研究差距，本研究旨在基于粒子群优化（PSO）元启发式方法开发MTA中生产订单的调度方法。调度方法旨在在具有相关设置时间的环境中最小化平均流动时间，设置时间和库存水平。为了评估新调度方法的性能，我们使用了计算仿真来比较该方法和MTA调度逻辑。结果表明，序列的PSO获得了更好的性能，减少了平均流动时间，建立时间和库存水平。