Two-sided assembly lines are widely utilized to assemble large-sized products such as cars and trucks. Recently, these types of assembly lines have been applied to assemble different types of products due to a large variety of customer demands and strong market competition. This paper presents two simple local search methods, the iterated greedy algorithm and iterated local search algorithm, to deal with type I mixed-model two-sided assembly line balancing problems. These two algorithms utilize new precedence-based local search functions with referenced permutation and two neighborhood structures to emphasize intensification while preserving high search speed. Additionally, these local search methods are enhanced by utilizing the best decoding scheme amongst nine candidates and a new station-oriented evaluation to guide the search direction. New lower bound calculations are also presented to check the optimality of the achieved solutions. Eleven recent and high-performing metaheuristic algorithms are re-implemented to test the performance of the proposed algorithms. A comprehensive study on a set of benchmark problems demonstrates the advantages of the improvements and the superiority of the two proposed methods. Experimental results show that the proposed algorithms obtain 23 new upper bounds compared with two recently published algorithms, among which 19 cases are proven to be optimal for the first time.

双面装配线被广泛用于装配大型产品，例如汽车和卡车。最近，由于各种各样的客户需求和强烈的市场竞争，这些类型的组装线已被用于组装不同类型的产品。本文提出了两种简单的局部搜索方法，即迭代贪婪算法和迭代局部搜索算法，以解决I型混合模型两侧装配线平衡问题。这两种算法利用具有参考置换和两个邻域结构的新的基于优先级的局部搜索功能来强调强度，同时保持较高的搜索速度。此外，这些本地搜索方法通过利用9个候选者之间的最佳解码方案和新的面向工作站的评估来指导搜索方向而得到增强。还提出了新的下界计算，以检查所获得解决方案的最优性。重新实现了11种最新的高性能元启发式算法，以测试所提出算法的性能。对一组基准问题的全面研究表明，改进的优点和所提出的两种方法的优越性。实验结果表明，与最近发布的两种算法相比，该算法获得了23个新的上限，其中有19个案例首次被证明是最优的。对一组基准问题的全面研究表明，改进的优点和所提出的两种方法的优越性。实验结果表明，与最近发布的两种算法相比，该算法获得了23个新的上限，其中有19个案例首次被证明是最优的。对一组基准问题的全面研究表明，改进的优点和所提出的两种方法的优越性。实验结果表明，与最近发布的两种算法相比，该算法获得了23个新的上限，其中有19个案例首次被证明是最优的。