Abstract The recovery of end of life (EOL) products has become an important issue in terms of economic as well as social and environmental considerations. Recent rigid environmental regulations also contribute to the popularity of disassembly and product recovery topics among academicians and practitioners. Disassembly lines have been utilised to break EOL products into pieces and remove parts which can be reused in the manufacturing of new products. However, to the best of the authors’ knowledge, there is no research on the two-sided disassembly lines, which are used for disassembly of large-sized products. Therefore, this research contributes to literature by introducing the two-sided disassembly line balancing problem (TDLBP) and modelling it mathematically for the first time. The problem is depicted and the challenges are explored through extensive numerical examples. Secondly, a powerful genetic algorithm approach, called 2-GA, is developed for solving the introduced TDLBP considering complex AND/OR precedence relations. Computational tests are conducted to test the performance of the proposed 2-GA and the results are compared to those obtained from CPLEX and tabu search algorithm. From the comparison of the obtained solutions, it can be concluded that 2-GA has a superior performance in finding optimal (or at least near-optimal) solutions usually within less than one second.

中文翻译：

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两侧拆卸线的平衡：问题定义、MILP 模型和遗传算法方法

摘要 报废 (EOL) 产品的回收已成为经济以及社会和环境考虑的重要问题。最近严格的环境法规也促进了拆卸和产品回收主题在院士和从业者中的流行。已使用拆卸线将 EOL 产品分解成碎片并移除可在新产品制造中重复使用的零件。然而，据作者所知，目前还没有关于用于大尺寸产品拆卸的双面拆卸线的研究。因此，本研究首次通过引入两侧拆卸线平衡问题 (TDLBP) 并对其进行数学建模，从而为文献做出贡献。通过大量的数值示例描述了问题并探索了挑战。其次，开发了一种强大的遗传算法方法，称为 2-GA，用于解决引入的 TDLBP，考虑到复杂的 AND/OR 优先关系。进行计算测试以测试所提出的 2-GA 的性能，并将结果与​​从 CPLEX 和禁忌搜索算法获得的结果进行比较。从获得的解决方案的比较中，可以得出结论，2-GA 通常在不到一秒的时间内在寻找最佳（或至少接近最佳）的解决方案方面具有优越的性能。进行计算测试以测试所提出的 2-GA 的性能，并将结果与​​从 CPLEX 和禁忌搜索算法获得的结果进行比较。从获得的解决方案的比较中，可以得出结论，2-GA 通常在不到一秒的时间内在寻找最佳（或至少接近最佳）的解决方案方面具有优越的性能。进行计算测试以测试所提出的 2-GA 的性能，并将结果与​​从 CPLEX 和禁忌搜索算法获得的结果进行比较。从获得的解决方案的比较中，可以得出结论，2-GA 通常在不到一秒的时间内在寻找最佳（或至少接近最佳）的解决方案方面具有优越的性能。