Production Scheduling (PS) is an essential paradigm within supply and manufacturing systems and an important element of sustainable development. PS, mainly known for its horizontal effects within the operational decision level, directly impacts both tactical and strategical levels of decision-making. In other words, an optimally designed and utilized PS module could bring efficiency towards the whole supply chain network of many manufacturing systems. Simulation Optimization (SO), as a growing Decision Support Tool (DST), provides a methodology required to drastically improve the efficiency of industrial systems. Thus, in this article, we review the existing research on SO Applied to PS (SOAPS), within the context of wider adaption of Industry 4.0 (known as the fourth industrial revolution). Firstly, relevant articles are examined and reviewed to position the research and develop research questions that enable the highlighting of research gaps. Then, a methodology was created based on: the studied PS problem features, proposed optimization frameworks, executed simulation tools, the SO architectures and the experimentation and validation strategies used. Finally, we investigate how Industry 4.0 could enhance the existing research on SOAPS to provide real-time and efficient SO-based DSTs for PS modules within modern manufacturing systems.

中文翻译：

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工业4.0时代模拟优化应用于生产调度：回顾与未来路线图

生产调度（PS）是供应和制造系统中的一个重要范例，也是可持续发展的重要组成部分。 PS主要以其在作战决策层面的横向影响而闻名，直接影响战术和战略层面的决策。换句话说，优化设计和使用的 PS 模块可以为许多制造系统的整个供应链网络带来效率。仿真优化 (SO) 作为不断发展的决策支持工具 (DST)，提供了大幅提高工业系统效率所需的方法。因此，在本文中，我们在工业 4.0（称为第四次工业革命）更广泛应用的背景下回顾了 SO 应用于 PS（SOAPS）的现有研究。首先，对相关文章进行审查和审查，以定位研究并提出研究问题，从而突出研究差距。然后，基于所研究的 PS 问题特征、提出的优化框架、执行的模拟工具、SO 架构以及所使用的实验和验证策略创建了一种方法。最后，我们研究工业 4.0 如何增强 SOAPS 的现有研究，为现代制造系统中的 PS 模块提供实时、高效的基于 SO 的 DST。