A Stochastic Programming Based Inventory Policy for Assemble-to-Order Systems with Application to the W Model

Doğru, Mustafa K.; Reiman, Marty I.; Wang, Qiong

doi:10.2139/ssrn.1332685

Cited by 19 publications

(39 citation statements)

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“…is a convex function minimization problem and, as such, computationally tractable, which result has already been established in the literature (see [26,8,30,47]). …”

Section: Basic Properties: Convexity and Sensitivitymentioning

confidence: 78%

“…Mohebbi and Choobineh [27] showed by simulation that such commonality benefits a manufacturer where supply and demand are uncertain. It is sometimes referred to as a "W" model [8] or an instance of a serial newsvendor network [46]. Additional details on our model are provided in Section 3.…”

Section: Assemble-to-order (Ato) Systemmentioning

confidence: 99%

“…Early papers in this area (e.g., [4,14,16]) compared the ATO and MTS systems for inventory reduction. Their models were extended to allow for capacity constraints [15], general demand distributions [10,50], asymmetric cost structures [30], and multiple periods [47,26,37,8]. Van Mieghem [46] showed that inventory reduction is still achieved, for fully correlated demands in which demand pooling is impossible, if two products have different profit margins and if the shared resource can choose the more profitable one.…”

Section: Assemble-to-order (Ato) Systemmentioning

confidence: 99%

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Sourcing assemble-to-order inventories under supplier risk uncertainty

Hong

Huh

Kang

2017

Omega

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“…is a convex function minimization problem and, as such, computationally tractable, which result has already been established in the literature (see [26,8,30,47]). …”

Section: Basic Properties: Convexity and Sensitivitymentioning

confidence: 78%

Section: Assemble-to-order (Ato) Systemmentioning

confidence: 99%

Section: Assemble-to-order (Ato) Systemmentioning

confidence: 99%

See 1 more Smart Citation

Sourcing assemble-to-order inventories under supplier risk uncertainty

Hong

Huh

Kang

2017

Omega

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“…To answer this we develop a new SP that constitutes a lower bound on the costs of the optimal base-stock policy under optimal allocation. This SP is obtained by adapting an idea proposed by Dogru et al (2010) to systems with unequal lead times. Results in the literature for single-component systems may lead one to believe that NV fractile asymmetry is the dominant factor determining the performance of FCFS (Topkis 1968).…”

Section: Introductionmentioning

confidence: 99%

Optimization of Industrial-Scale Assemble-to-Order Systems

Jaarsveld

Scheller‐Wolf

2015

INFORMS Journal on Computing

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U sing a novel stochastic programming (SP) formulation, we develop an algorithm for inventory control in industrial-size assemble-to-order (ATO) systems that has unparalleled efficiency and scalability. Applying our algorithm to several numerical examples, we generate new insights regarding the control and optimization of these systems.We consider a continuous time model, seeking base-stock levels for components that minimize the sum of holding costs and product-specific backorder costs. Our initial focus is on first-come, first-served (FCFS) allocation of components to products; for this setting our algorithm quickly computes solutions for which the asymptotic optimality gap with the optimal FCFS base-stock policy is less than 1%. We then turn to two related questions: How do common heuristics used in practice compare to our performance, and how costly is the FCFS assumption?For the first question, we investigate the effectiveness of ignoring simultaneous stock-outs (ISS), a heuristic that has been used by companies such as IBM and Dell. Our experiments indicate that ISS performance, when compared to the optimal FCFS base-stock policy, improves as the average newsvendor (NV) fractiles increase but suffers under lead-time demand correlations.For the second question, we develop an efficiently computable upper bound on the benefit of optimal allocation over FCFS. We find that for many large ATO systems, FCFS performs surprisingly well and that its performance improves with decreasing NV fractile asymmetry among products and, again, with increasing average NV fractiles. We also investigate simple no-holdback allocation policies and find that they tend to outperform the best FCFS policies.

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“…Glasserman and Wang (1998) consider ATO systems with batch demand arrivals that are modelled as a set of M X /G/1 and G X /G/1 queues. Other papers in this category include the work of Zhao (2009), Lu, Song, andZhao (2010) and Doğru, Reiman, and Wang (2010).…”

Section: Introductionmentioning

confidence: 99%

An assemble-to-order system with product and components demand with lost sales

Elhafsi

Camus

et al. 2014

International Journal of Production Research

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This paper studies a single end product assemble-to-order system serving both the demand of the end product and the individual components. Demands are assumed to form independent Poisson streams with different rates. Unsatisfied demand, both for the end product and for components, is assumed lost and thus incurs a per unit lost sale penalty. The end product is assembled from K distinct components each produced on a different production facility (or procured from independent suppliers). Production lead times are non-identical and are assumed to be independent and exponentially distributed. Produced components are held in stock in anticipation of future demands. The goal is to determine the optimal component production and inventory allocation policy. The optimal policy is characterised using a Markov Decision Process model. It is shown that, in addition to the state-dependent threshold type, the optimal policy exhibits counterintuitive features which have not been observed in systems without components demand. In particular, for certain combinations of system parameters, the optimal inventory allocation policy switches priority as the inventory level of components changes. Furthermore, for a particular component k, as the inventory level of other components increases, the desirability of satisfying Component k demand decreases. Finally, because in general the optimal policy is fairly complicated and is difficult to obtain numerically, due to the curse of dimensionality of dynamic programming, three heuristic policies are proposed. Extensive numerical experiments indicate that the three heuristics perform very well compared to the optimal policy.

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A Stochastic Programming Based Inventory Policy for Assemble-to-Order Systems with Application to the W Model

Cited by 19 publications

References 0 publications

Sourcing assemble-to-order inventories under supplier risk uncertainty

Sourcing assemble-to-order inventories under supplier risk uncertainty

Optimization of Industrial-Scale Assemble-to-Order Systems

An assemble-to-order system with product and components demand with lost sales

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