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Multi-Criteria Decision Making For Disassembly-To-Order System Under Stochastic Yields

机译：随机产量下按订单生产系统的多准则决策

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摘要

In this paper, we consider the problem of determining the optimal number of returned products to disassemble to fulfill the demand for a specified number of parts. This is known as the disassembly-to-order (DTO) problem. The deterministic yield version of this problem has been addressed in the literature. Recently, the stochastic yield version of this problem with a single objective has also been reported in the literature. In this paper, we extend the methodology to include multiple objectives. To this end, we model the DTO problem using integer goal programming. The stochastic problem is solved by transforming it into its deterministic equivalent problem. This conversion is accomplished by considering the specific structures of the products with one core and one part ("one-to-one structure") and apply it to handle the products with one core and multiple parts ("one-to-many structure"). For these special cases it is possible to solve the stochastic problem analytically so that valuable insights can be gained by comparing the stochastic and deterministic solutions. This will help us to determine effective deterministic yield equivalents. We present a case example to illustrate the methodology.
机译：在本文中，我们考虑确定可拆卸的退货产品的最佳数量，以满足特定数量零件的需求的问题。这被称为按订单拆卸（DTO）问题。该问题的确定性屈服版本已在文献中讨论。最近，文献中还报道了具有单个目标的该问题的随机产量形式。在本文中，我们将方法论扩展到包括多个目标。为此，我们使用整数目标编程对DTO问题进行建模。随机问题可以通过将其转化为确定性的等效问题来解决。通过考虑具有一个核心和一个部分的产品的特定结构（“一对一结构”）并将其应用于处理具有一个核心和多个部分的产品（“一对多结构”）来完成此转换。 ）。对于这些特殊情况，可以通过分析解决随机问题，从而通过比较随机和确定性解决方案可以获得有价值的见解。这将帮助我们确定有效的确定性产量当量。我们提供一个案例来说明该方法。

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