Joint Inventory Replenishment and Component Allocation Optimization in an Assemble-to-Order System

Akçay, Yalçın; Xu, Susan H.

doi:10.1287/mnsc.1030.0167

Cited by 89 publications

(32 citation statements)

References 23 publications

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“…These limited results suggest that it can be beneficial to hold back inventory to fill complete work-orders. We note also that it has been pointed out that this allocation decision should be jointly optimized with the inventory control decision (Akçay and Xu, 2004).…”

Section: Spare Parts Order Handling Literaturementioning

confidence: 93%

“…We already pointed out that this allocation problem is similar to the one found in assemble-to-order (ATO) systems. This problem is known in general to be NP-hard (Akçay and Xu, 2004) even without the stochasticity involved in demand. Also in the present context the question of when, whether and how to hold back spare parts in order to fill complete work orders is still an open question for which only limited results are available (Lu et al, 2010).…”

Section: Spare Parts Order Handling Literaturementioning

confidence: 99%

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Maintenance spare parts planning and control: a framework for control and agenda for future research

Driessen

Arts

Houtum

et al. 2014

Production Planning & Control

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. (2010). Maintenance spare parts planning and control : a framework for control and agenda for future research. (BETA publicatie : working papers; Vol. 325). Eindhoven: Technische Universiteit Eindhoven. General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.• Users may download and print one copy of any publication from the public portal for the purpose of private study or research.• You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal ? Take down policyIf you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. Abstract This paper presents a framework for planning and control of the spare parts supply chain in organizations that use and maintain high-value capital assets. Decisions in the framework are decomposed hierarchically and interfaces are described. We provide relevant literature to aid decision making and identify open research topics. The framework can be used to increase the efficiency, consistency and sustainability of decisions on how to plan and control a spare parts supply chain. Applicability of the framework in different environments is investigated.

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Section: Spare Parts Order Handling Literaturementioning

confidence: 93%

Section: Spare Parts Order Handling Literaturementioning

confidence: 99%

Maintenance spare parts planning and control: a framework for control and agenda for future research

Driessen

Arts

Houtum

et al. 2014

Production Planning & Control

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show abstract

“…These include a fixed priority rule (Zhang 1997), the FCFS rule (Hausman et al 1998), and a fair-share rule (Agrawal and Cohen 2001). Akcay and Xu (2004) studied a product-based allocation rule that makes optimal or near-optimal allocation decisions within each period. However, all these prior studies apply FCFS to demand between periods.…”

Section: Literature Reviewmentioning

confidence: 99%

No-Holdback Allocation Rules for Continuous-Time Assemble-to-Order Systems

Song

Zhao

2010

Operations Research

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This paper analyzes a class of common-component allocation rules, termed no-holdback (NHB) rules, in continuous-review assemble-to-order (ATO) systems with positive lead times. The inventory of each component is replenished following an independent base-stock policy. In contrast to the usually assumed first-come-first-served (FCFS) component allocation rule in the literature, an NHB rule allocates a component to a product demand only if it will yield immediate fulfillment of that demand. We identify metrics as well as cost and product structures under which NHB rules outperform all other component allocation rules. For systems with certain product structures, we obtain key performance expressions and compare them to those under FCFS. For general product structures, we present performance bounds and approximations. Finally, we discuss the applicability of these results to more general ATO systems.Subject classifications: stochastic multi-item inventory system; assemble-to-order; base-stock policy; common-component allocation rule; non-FCFS; sample-path analysis.

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“…As a result, simple heuristic control policies for general ATO systems are attracting widespread interest in practice (Lu et al 2010). Likewise, several researchers have explored performance evaluation and optimization techniques of various heuristic policies; see, for instance, Zhang (1997), Agrawal and Cohen (2001), and Akcay and Xu (2004). We refer the reader to Song and Zipkin (2003) for a comprehensive review of this literature.…”

Section: Introductionmentioning

confidence: 99%

Experimental Results Indicating Lattice-Dependent Policies May Be Optimal for General Assemble-to-Order Systems

Nadar¹,

Akan²,

Scheller‐Wolf³

2015

SSRN Journal

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We consider an assemble-to-order (ATO) system with multiple products, multiple components which may be demanded in different quantities by different products, possible batch ordering of components, random lead times, and lost sales. We model the system as an infinite-horizon Markov decision process under the average cost criterion. A control policy specifies when a batch of components should be produced, and whether an arriving demand for each product should be satisfied. Previous work has shown that a lattice-dependent base-stock and lattice-dependent rationing (LBLR) policy is an optimal stationary policy for a special case of the ATO model presented here (the generalized M -system).In this paper, we conduct numerical experiments to evaluate the use of an LBLR policy for our general ATO model as a heuristic, comparing it to two other heuristics from the literature: a state-dependent basestock and state-dependent rationing (SBSR) policy, and a fixed base-stock and fixed rationing (FBFR) policy. Remarkably, LBLR yields the globally optimal cost in each of more than 22,500 instances of the general problem, outperforming SBSR and FBFR with respect to both objective value (by up to 2.6% and 4.8%, respectively) and computation time (by up to three orders and one order of magnitude, respectively) in 350 of these instances (those on which we compare the heuristics). LBLR and SBSR perform significantly better than FBFR when replenishment batch sizes imperfectly match the component requirements of the most valuable or most highly demanded product. In addition, LBLR substantially outperforms SBSR if it is crucial to hold a significant amount of inventory that must be rationed.

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Joint Inventory Replenishment and Component Allocation Optimization in an Assemble-to-Order System

Abstract: doi 10.1287/mnsc.1030.016

Cited by 89 publications

References 23 publications

Maintenance spare parts planning and control: a framework for control and agenda for future research

Maintenance spare parts planning and control: a framework for control and agenda for future research

No-Holdback Allocation Rules for Continuous-Time Assemble-to-Order Systems

Experimental Results Indicating Lattice-Dependent Policies May Be Optimal for General Assemble-to-Order Systems

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