The capital goods industry produces physical assets used for current and future production. Capital goods are highly customised. Production scheduling aims to synchronise material supply, component manufacturing, sub-assembly and final assembly processes to minimise the total costs of earliness and tardiness, whilst satisfying finite capacity, machining and assembly precedence constraints. This paper presents the first application of Grey Wolf Optimisation (GWO) together with modified and hybridised versions for solving the capital goods scheduling problem. A novel GWO-based production scheduling tool was developed and validated using four realistic case studies obtained from a collaborating company. The first experiment identified appropriate parameter settings for the GWO. The performance of the GWO was then evaluated and compared with a modified GWO and a hybridised GWO. The computational results obtained from the proposed methods were statistical analysed. The outperformed other metaheuristics.

资本货物行业生产用于当前和未来生产的有形资产。资本货物高度定制。生产计划的目的是使材料供应，零件制造，子装配和最终装配过程同步，以最大程度地减少提早和拖延的总成本，同时满足有限的产能，加工和装配优先顺序的限制。本文介绍了灰狼优化（GWO）以及修改和混合版本在解决资本货物调度问题中的首次应用。开发了一种新颖的基于GWO的生产计划工具，并使用了从一家合作公司获得的四个实际案例研究进行了验证。第一个实验确定了GWO的适当参数设置。然后评估GWO的性能，并将其与改良的GWO和杂交的GWO进行比较。从提出的方法获得的计算结果进行了统计分析。胜过其他元启发法。