Abstract As the disassembly of end-of-life products is affected by several dynamic and uncertain issues, many mathematical models and solution approaches have been established. However, with more extended objectives, constraints and different methods of disassembly, inconsistent models relating to product representations and types of disassembly lines have become the main barriers for the transfer of research to practise. In this paper, a systematic overview of recent models to summarise the input data, parameters, decision variables, constraints and objectives of disassembly line balancing are presented. After discussing the adaptation and extensibility of these models for different environments, a unified encoding scheme is designed to apply typical multi-objective evolutionary algorithms on this problem with extensive decision variables and seven significant objectives. Algorithm comparison on four typical cases is then carried out based on seven commonly used products to verify the optimisation process for the integrated version of existing models and demonstrate the overall performance of the typical multi-objective evolutionary algorithms on this problem. Experimental results can be a baseline for further algorithm design and practical algorithm selection on these disassembly line balancing scenarios.

中文翻译：

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多目标拆装线平衡模型回顾与算法比较

摘要 由于报废产品的拆解受到多种动态和不确定性问题的影响，人们建立了许多数学模型和解决方法。然而，随着更多扩展的目标、约束和不同的拆卸方法，与产品表示和拆卸线类型相关的不一致模型已成为将研究转移到实践的主要障碍。在本文中，系统概述了最近的模型，以总结拆卸线平衡的输入数据、参数、决策变量、约束和目标。在讨论了这些模型对不同环境的适应性和可扩展性之后，统一编码方案旨在将典型的多目标进化算法应用于具有广泛决策变量和七个重要目标的问题。然后基于7个常用产品对4个典型案例进行算法对比，验证现有模型集成版本的优化过程，展示典型多目标进化算法在该问题上的整体性能。实验结果可以作为这些拆装线平衡场景下进一步算法设计和实用算法选择的基准。然后基于7个常用产品对4个典型案例进行算法对比，验证现有模型集成版本的优化过程，展示典型多目标进化算法在该问题上的整体性能。实验结果可以作为这些拆装线平衡场景下进一步算法设计和实用算法选择的基准。然后基于7个常用产品对4个典型案例进行算法对比，验证现有模型集成版本的优化过程，展示典型多目标进化算法在该问题上的整体性能。实验结果可以作为这些拆装线平衡场景下进一步算法设计和实用算法选择的基准。