Research in assembly optimisation is presently inclined towards integrative measures. Several benefits of simultaneously optimised Assembly Sequence Planning (ASP) and Assembly Line Balancing (ALB) have been highlighted by researchers to have better solution quality, shorter time-to-market, and minimalised error during planning. Recently, several efforts have been made to realise integrated assembly optimisation. However, none of the published research considered the two-sided assembly line problem. This paper presents an integrated ASP and ALB optimisation in a two-sided assembly environment (2S-ASPLB), which is mainly adopted in automotive assembly process. In this study, the 2S-ASPLB problem was formulated and optimised using Multi-Objective Multi-Verse Optimiser (MOMVO) by considering line efficiency, reorientation penalty, and tool change as the optimisation objectives. The computational experiments were conducted in a few stages, beginning with the identification of the best decoding approach for 2S-ASPLB. Next, the best MOMVO coefficient was studied, followed by comparing MOMVO performance with well-established multi-objective optimisation algorithms. Finally, a case study problem was presented to demonstrate applicability of the proposed model and algorithm in real-life problem. The results indicated that the priority factor (PF) decoding approach had better performance compared with others. Meanwhile, in comparison with well-established algorithms, MOMVO performed better in convergence and solution distribution. The case study results indicated the applicability of proposed 2S-ASPLB model and algorithm to improve line efficiency in assembly line. The main contribution of the research is a new 2S-ASPLB model and optimisation scheme, which can assist manufacturer in designing better assembly layout.

装配优化的研究目前倾向于综合措施。研究人员强调了同时优化的装配顺序规划 (ASP) 和装配线平衡 (ALB) 的几个好处，即在规划过程中具有更好的解决方案质量、更短的上市时间和最小的错误。最近，已经做出了一些努力来实现集成装配优化。然而，已发表的研究均未考虑双边装配线问题。本文提出了一种双边装配环境（2S-ASPLB）中的集成 ASP 和 ALB 优化，主要用于汽车装配过程。在这项研究中，2S-ASPLB 问题通过考虑线路效率、重新定向惩罚、和工具更换作为优化目标。计算实验分几个阶段进行，从确定 2S-ASPLB 的最佳解码方法开始。接下来，研究了最佳 MOMVO 系数，然后将 MOMVO 性能与成熟的多目标优化算法进行了比较。最后，提出了一个案例研究问题，以证明所提出的模型和算法在实际问题中的适用性。结果表明，与其他方法相比，优先因子（PF）解码方法具有更好的性能。同时，与成熟的算法相比，MOMVO 在收敛和解分布方面表现更好。案例研究结果表明所提出的 2S-ASPLB 模型和算法在提高装配线效率方面的适用性。