Determination of safety stocks in a lost sales inventory system with periodic review, positive lead-time, lot-sizing and a target fill rate

Donselaar, KH Karel van; Broekmeulen, Racm Rob

doi:10.1016/j.ijpe.2011.05.020

Cited by 35 publications

(12 citation statements)

References 25 publications

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“… [93] ; Sarkar et al. [94] ; Sana and Chaudhuri [95] ; Ruiz-Torres and Mahmoodi [61] ; Hayya and Harrison [96] ; Zhou and Viswanathan [97] ; Chakraborty and Giri [98] ; Van Donselaar and Broekmeulen [99] ; Chaturvedi and Martínez-de-Albéniz [100] ; Manzini et al. [101] ; Huang et al.…”

Section: Category Selection and Materials Evaluationmentioning

confidence: 99%

“…The stochastic models for dimensioning safety stocks are firmly grounded in probability and statistical theory applied to inventory management, including queueing theory and Markov chains. Van Donselaar and Broekmeulen [99] determined safety stocks in a lost sales periodic review inventory control system with stochastic discrete demands. Linear regression was employed to propose fast approximations for the fill rate.…”

Section: Category Selection and Materials Evaluationmentioning

confidence: 99%

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Operations research models and methods for safety stock determination: A review

Gonçalves

Carvalho

Cortez

2020

Operations Research Perspectives

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Highlights A review on operations research (OR) models and methods for safety stock determination is conducted. No work has yet systematized research focusing on the safety stock determination problem. Articles are classified and discussed regarding the modeling approach, industrial application, solution technique and main performance criteria used. Research opportunities, promising research directions and trends are identified.

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Section: Category Selection and Materials Evaluationmentioning

confidence: 99%

Section: Category Selection and Materials Evaluationmentioning

confidence: 99%

Operations research models and methods for safety stock determination: A review

Gonçalves

Carvalho

Cortez

2020

Operations Research Perspectives

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“…However, Eq. 3is chosen as an appropriate proxy for safety stock calculation, because service level requirements are very high in the considered case study (see [4] for a comprehensive review of lost sales inventory theory and [26] for a numerical analysis of safety stock calculation formulas).…”

Section: Simulation Modelmentioning

confidence: 99%

Performance- and value-oriented decision support for supply chain configuration

et al. 2014

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The task of supply chain (SC) configuration is to establish a product-specific SC for new products. Apart from cross-regional network aspects and inter-disciplinary factors, the problem complexity is driven by dynamics and uncertainties of short product life cycles. SC configuration affects SC performance and value creation. Hence, resulting impacts have to be measured and compared under consideration of dynamics and uncertainties. In the conceptual part of this paper, dynamics and uncertainties of SC configuration are integrated into a conceptual framework for value-based supply chain management. In the modelbased part of this paper, this framework is linked to a discrete-event simulation model. The performance outcomes and value impacts of SC configuration options are empirically assessed in a case study of a fast-moving consumer goods manufacturer. The shortfalls of costfocused decision-making without consideration of capitalrelated factors and non-financial aspects are illustrated.

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“…Zipkin (2008a) showed that the inventory costs could be inflated by up to 30% by using theory developed from linear backlogging models in nonlinear lostsales settings. Also, Van Donselaar and Broekmeulen (2013) provided evidence that backorder models dramatically over-estimate the safety stock needed in lost-sales systems. Importantly, Huh et al (2009) showed that the linear approximation of lost-sales inventory systems is only valid under strictly defined conditions.…”

Section: Introductionmentioning

confidence: 99%

Exploring the nonlinear dynamics of the lost-sales order-up-to policy

Disney

Ponte

Wang

2020

International Journal of Production Research

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With most inventory theory investigating linear models, the dynamics of nonlinear inventory systems is not well understood. We explore the dynamics of the order-upto policy under lost-sales for the case of i.i.d. normally distributed demand and unit lead times. We consider the ideal minimum mean squared error forecast and two alternative scenarios: partial demand observation and dynamic demand forecasting, providing a broad understanding of the operational performance of lost-sales systems. In each scenario, we obtain analytical expressions for the order, inventory, and satisfied demand distributions. This allows us to quantify the Bullwhip and inventory variance amplification ratios as well as the fill rate and the inventory cover. We show the lost sales nonlinearity induces complex behaviors in inventory systems. Interestingly, lost sales smooth supply chain dynamics, significantly affecting the trade-off between service level and average inventory holding. We also reveal the inventory downsides of demand censoring and the production damages induced by dynamic forecasts. We identify a key parameter, the relative safety margin, that characterizes the performance of lost-sales systems. We finish by offering some prescriptive results for the optimal safety stock and capacity level in both a retail and a manufacturing lost-sales setting.

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Determination of safety stocks in a lost sales inventory system with periodic review, positive lead-time, lot-sizing and a target fill rate

Abstract: Determination of safety stocks in a lost sales inventory system with periodic review, positive lead-time, lot-sizing and a target fill rate. (BETA publicatie : working papers; Vol. 336). Technische Universiteit Eindhoven.

Cited by 35 publications

References 25 publications

Operations research models and methods for safety stock determination: A review

Operations research models and methods for safety stock determination: A review

Performance- and value-oriented decision support for supply chain configuration

Exploring the nonlinear dynamics of the lost-sales order-up-to policy

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