Abstract The disassembly process has attracted mounting interest due to growing green concerns. This paper addresses the capacitated dynamic lot-sizing problem with external procurement, defective and backordered items, setup times, and extra capacity. The problem is to determine how many end-of-life products to disassemble during each period. We propose a new mixed-integer programming (MIP) approach to formulate the problem under study in order to maximize the disassembly-process gain, which is obtained as the difference between the revenue achieved by resale of the items recovered after disassembly and the costs tied to operating the disassembly tasks. Several numerical tests using the well-known CPLEX solver proved that this new model can find the optimal disassembly schedule for most test instances within an acceptable computational time. Furthermore, we led sensitivity studies on disassembly capacity, setup time and procurement cost. Test results validate the power of the suggested model and provide helpful insights for industry practitioners.

中文翻译：

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新的混合整数方法来解决具有缺陷项目和积压的多级容量拆卸批量问题

摘要 由于日益增长的绿色关注，拆卸过程引起了越来越多的兴趣。本文解决了外部采购、缺陷和缺货项目、设置时间和额外产能的动态批量调整问题。问题是确定在每个时期要拆卸多少报废产品。我们提出了一种新的混合整数规划 (MIP) 方法来制定正在研究的问题，以最大化拆卸过程收益，这是通过拆卸后回收的物品转售所获得的收入与相关成本之间的差额获得的操作拆卸任务。使用著名的 CPLEX 求解器进行的多项数值测试证明，这种新模型可以在可接受的计算时间内为大多数测试实例找到最佳拆卸计划。此外，我们还对拆卸能力、设置时间和采购成本进行了敏感性研究。测试结果验证了建议模型的能力，并为行业从业者提供了有用的见解。