With the development of society and technology, the modern manufacturing system is required to handle unpredictable and rapidly changing market demands during various demand periods. This is a new challenge to the production scheduling of the production line, which requires a faster and smarter response to changes in production demand. To meet the challenge, the reconfigurable manufacturing system (RMS) has emerged as a competitive and promising manufacturing model. The reconfigurable assembly system (RAS), a critical feature of RMS, can be seamlessly incorporated into multi-variety, variable-batch, multi-functional, and fast-delivery manufacturing modes, opening up the possibility of rapid changes for production scheduling. In this paper, we first build a RAS model that can more accurately represent scheduling problems that may occur in real-world industrial operations. More specifically, we consider the assembly process of products could be divided into a number of major steps which are performed in different stations and optimize the assembly sequence of products and the equipment selection within individual assembly stations. After that, three objective functions corresponding to the workload balance, reconfiguration/assembly cost, and lead time are proposed to jointly optimize the assembly sequence and the equipment selection in individual assembly stations. Finally, a hybrid particle swarm optimization (MOHPSO) method is utilized to solve the multiple-objective optimization problem, which combines the advantages of particle swarm optimization and the hybrid method. Experimental results show the superiority of the proposed MOHPSO method over other alternatives including MOPSO and NSGA-II, achieving lower Spacing Metric (SM) and Mean Ideal Distance (MID) indexes and is suitable for solving production scheduling problems.

随着社会和技术的发展，现代制造系统需要在各个需求时期应对不可预测和快速变化的市场需求。这是对产线生产调度的新挑战，需要更快速、更智能地响应生产需求的变化。为了应对挑战，可重构制造系统 (RMS) 已成为一种具有竞争力和前景广阔的制造模式。可重构装配系统（RAS）是RMS的关键特性，可以无缝融入多品种、多批次、多功能、快速交付的制造模式，为生产调度的快速变化开辟了可能性。在本文中，我们首先建立了一个 RAS 模型，可以更准确地表示现实世界工业运营中可能出现的调度问题。更具体地说，我们认为产品的组装过程可以分为多个主要步骤，这些步骤在不同的工作站中执行，并优化产品的组装顺序和各个组装工作站内的设备选择。之后，提出了与工作量平衡、重新配置/组装成本和交货时间相对应的三个目标函数，以联合优化各个组装站的组装顺序和设备选择。最后，结合粒子群优化和混合方法的优点，利用混合粒子群优化（MOHPSO）方法解决多目标优化问题。