On assemble-to-order systems with flexible customers

Abstract

We consider an assemble-to-order system in which each customer order consists of a mix of key and non-key items. Key items are items where the customer is lost if one or more of his key items are not available. The non-key items are items which are not essential, and therefore, customers may ignore those items if they are not available. We also allow substitution in our model, and assume that some proportion of customers accept substitutions for missing items. We then develop a quasi-birth-and-death process which can be used to obtain the performance measures of the assemble-to-order system. We also introduce new measures which evaluate different levels of customer satisfaction. Through a numerical study, we reveal some interesting behaviors of the system and explore the underlying causes.

Comparing Markov Chains: Aggregation and Precedence Relations Applied to Sets of States, with Applications to Assemble-to-Order Systems

“…Although loss networks have a product-form solution (Ross [33]), exactly computing the blocking probabilities for this system is known to be a #P-complete problem (Louth et al [23]) due to the normalizing constant. [14] Li and Xu [21], Xu [50] Li and Xu [21], Xu [50] Iravani et al [13] Dayanik et al [8] Song and Yao [38] Iravani et al [13] Lu et al [25] Lu et al [26], Lu [24] B. Joint…”

“…Dayanik et al [8] presented several approximations and bounds on the performance of ATO systems. Furthermore, the ATO-POS model is another special case of the model discussed in Iravani et al [13].…”

“…This exact method, however, needs a considerable amount of time for large problem instances. Iravani et al [13] extended the model of Song et al by allowing customers to be selective and/or flexible. Selective customers are not going to buy the final product unless all key items are available.…”

“…Flexible customers are willing to substitute one or more nonavailable items by an item that is available. The ATO-TOS model is a special case of the model of Iravani et al [13].…”

Quantifying input uncertainty in an assemble-to-order system simulation with correlated input variables of mixed types

“…Assemble-to-order systems have been widely studied in the supply chain management literature (Glasserman and Wang 1998, Cheng, Ettl, Lin, and Yao 2002, Iravani, Luangkesorn, and Simchi-Levi 2003. We will consider a modified version of the ATO system studied by Hong and Nelson (2006).…”