Divergence control of a one-level supply chain replenishment rule

Strozzi, Fernanda; Noè, Carlo; Zaldı́var, J.M.

doi:10.1080/00207543.2011.565087

Cited by 5 publications

(4 citation statements)

References 33 publications

Supporting

Mentioning

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Order By: Relevance

“…This effect refers to the phenomenon occurring when the orders from the supplier have larger variance than the ones from the customers, i.e. variance amplification (Strozzi et al 2012). This is known to inevitably lead to excessive inventory investment, poor customer service, lost revenues, misguided capacity plans, ineffective transportation, and missed production schedules (Chen et al 2012).…”

Section: Introductionmentioning

confidence: 99%

On bullwhip-limiting strategies in divergent supply chain networks

Domínguez¹,

Cannella²,

Framiñán³

2014

Computers & Industrial Engineering

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Section: Introductionmentioning

confidence: 99%

On bullwhip-limiting strategies in divergent supply chain networks

Domínguez¹,

Cannella²,

Framiñán³

2014

Computers & Industrial Engineering

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“…They derived the controllable and observable state space model using an exponential smoothing delay without losing generality. The state space approach was also adopted by Strozzi et al (2012), who explored the divergence of a logistic chain model within the OUT policy.…”

Section: The Optimisation Of Decision Parameters In the Iobpcs Familymentioning

confidence: 99%

The extension and exploitation of the inventory and order based production control system archetype from 1982 to 2015

Lin

Naim

Purvis

2017

International Journal of Production Economics

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In 1994, through classic control theory, John, Naim and Towill developed the 'Automatic Pipeline, Inventory and Order-based Production Control System' (APIOBPCS) which extended the original IOBPCS archetype developed by Towill in 1982 ─ well-recognized as a base framework for a production planning and control system. Due to the prevalence of the two original models in the last three decades in the academic and industrial communities, this paper aims to systematically review how the IOBPCS archetypes have been adopted, exploited and adapted to study the dynamics of individual production planning and control systems and whole supply chains. Using various databases such as Scopus, Web of Science, Google Scholar (111 papers), we found that the IOBPCS archetypes have been studied regarding the a) modification of four inherent policies related to forecasting, inventory, lead-time and pipeline to create a 'family' of models, b) adoption of the IOBPCS 'family' to reduce supply chain dynamics, and in particular bullwhip, c) extension of the IOBPCS family to represent different supply chain scenarios such as order-book based production control and closed-loop processes. Simulation is the most popular method adopted by researchers and the number of works based on discrete time based methods is greater than those utilizing continuous time approaches. Most studies are conceptual with limited practical applications described. Future research needs to focus on cost, flexibility and sustainability in the context of supply chain dynamics and, although there are a few existing studies, more analytical approaches are required to gain robust insights into the influence of nonlinear elements on supply chain behaviour. Also, empirical exploitation of the existing models is recommended.

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“…Equation models the order rule adopted in our model. The order rule is a well‐known variant of a periodic review Order‐Up‐To (OUT), namely, a smoothing replenishment rule (Boute et al., ; Bijulal et al., ; Strozzi et al., ). The features of smoothing replenishment rules were studied and popularized by Towill (), John et al.…”

Section: The Coordinated Decentralized Linear Sc Modelmentioning

confidence: 99%

A simulation model of a coordinated decentralized supply chain

Cannella

López-Campos

Domínguez

et al. 2015

Int Trans Operational Res

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This paper presents a simulation-based study of a coordinated, decentralized linear supply chain (SC) system. In the proposed model, any supply tier considers its successors as part of its inventory system and generates replenishment orders on the basis of its partners' operational information. We show that the proposed coordinated decision-making process creates a reduction in information distortion along an SC compared with a traditional, noncoordinated strategy. A novel result is that we show how a coordinated SC can avoid the detrimental consequences of demand amplification in terms of penalty costs due to the stockout phenomenon in upstream stages.

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Divergence control of a one-level supply chain replenishment rule

Cited by 5 publications

References 33 publications

On bullwhip-limiting strategies in divergent supply chain networks

On bullwhip-limiting strategies in divergent supply chain networks

The extension and exploitation of the inventory and order based production control system archetype from 1982 to 2015

A simulation model of a coordinated decentralized supply chain

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