Purpose

Due to the market trend of low-volume and high-variety, the manufacturing industry is paying close attention to improve the ability to hedge against variability. Therefore, in this paper the assembly line with limited resources is balanced in a robust way that has good performance under all possible scenarios. The proposed model allows decision makers to minimize a posteriori regret of the selected choice and hedge against the high cost caused by variability.

Design/methodology/approach

A generalized resource-constrained assembly line balancing problem (GRCALBP) with an interval data of task times is modeled and the objective is to find an assignment of tasks and resources to the workstations such that the maximum regret among all the possible scenarios is minimized. To properly solve the problem, the regret evaluation, an exact solution method and an enhanced meta-heuristic algorithm, Whale Optimization Algorithm, are proposed and analyzed. A problem-specific coding scheme and search mechanisms are incorporated.

Findings

Theory analysis and computational experiments are conducted to evaluated the proposed methods and their superiority. Satisfactory results show that the constraint generation technique-based exact method can efficiently solve instances of moderate size to optimality, and the performance of WOA is enhanced due to the modified searching strategy.

Originality/value

For the first time a minmax regret model is considered in a resource-constrained assembly line balancing problem. The traditional Whale Optimization Algorithm is modified to overcome the inferior capability and applied in discrete and constrained assembly line balancing problems.

中文翻译：

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运行时间不确定的资源受限装配线平衡问题的鲁棒优化

目的

由于市场向小批量、多品种发展的趋势，制造业正在密切关注提高对冲变数的能力。因此，在本文中，资源有限的装配线以一种稳健的方式平衡，在所有可能的情况下都具有良好的性能。所提出的模型允许决策者最小化所选选择的后验遗憾，并对冲由可变性引起的高成本。

设计/方法/方法

对具有任务时间间隔数据的广义资源受限装配线平衡问题 (GRCALBP) 进行建模，目标是找到任务和资源到工作站的分配，以使所有可能场景中的最大遗憾最小化。为正确解决该问题，提出并分析了遗憾评估、精确求解方法和增强的元启发式算法鲸鱼优化算法。结合了特定问题的编码方案和搜索机制。

发现

进行理论分析和计算实验以评估所提出的方法及其优越性。令人满意的结果表明，基于约束生成技术的精确方法可以有效地将中等大小的实例求解到最优，并且由于改进了搜索策略，WOA的性能得到了提高。

原创性/价值

首次在资源受限的装配线平衡问题中考虑最小最大遗憾模型。对传统的鲸鱼优化算法进行了修改，以克服能力较差的问题，并将其应用于离散和受约束的装配线平衡问题。