Inventory control in case of unknown demand distribution

Bulinskaya, Ekaterina

doi:10.1016/0167-188x(90)90056-n

Cited by 12 publications

(5 citation statements)

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“…If a priori information about the unknown distribution is absent, then the natural approach proposed in [12] consists in replacing the predicted distributions with empirical ones. This involves various problems, for example, due to the accuracy of the approximations of unknown distributions.…”

Section: Final Remarksmentioning

confidence: 99%

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Cost and Reliability Approaches in Inventory Theory

Bulinskaya

2005

Cybern Syst Anal

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Section: Final Remarksmentioning

confidence: 99%

“…Remark 2. To solve system (12), it is proposed to use the method of successive approximations, namely, put (8), which can easily be verified.…”

Section: Asymptotically Optimalmentioning

confidence: 99%

Cost and Reliability Approaches in Inventory Theory

Bulinskaya

2005

Cybern Syst Anal

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“…In addition to the periodic inventory systems (Syntetos and Boylan, 2006) and the incomplete demand information (Bulinskaya, 1990;Janssen et al, 2009), in this study, the data quality has been shown to cover the supply information and to be relevant for a continuously reviewed inventory policy as well.…”

Section: Theoretical Implicationsmentioning

confidence: 99%

“…only the first couple of moments of the demand distribution are known; and . nothing about the demand distribution is known (Bulinskaya, 1990).…”

Section: Introductionmentioning

confidence: 99%

Exploring incomplete information in maintenance materials inventory optimization

Puurunen

Majava

Kess

2014

Industrial Management &Amp; Data Systems

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Purpose – Ensuring the sufficient service level is essential for critical materials in industrial maintenance. This study aims to evaluate the use of statistically imperfect data in a stochastic simulation-based inventory optimization where items' failure characteristics are derived from historical consumption data, which represents a real-life situation in the implementation of such an optimization model. Design/methodology/approach – The risks of undesired shortages were evaluated through a service-level sensitivity analysis. The service levels were simulated within the error of margin of the key input variables by using StockOptim optimization software and real data from a Finnish steel mill. A random sample of 100 inventory items was selected. Findings – Service-level sensitivity is item specific, but, for many items, statistical imprecision in the input data causes significant uncertainty in the service level. On the other hand, some items seem to be more resistant to variations in the input data than others. Research limitations/implications – The case approach, with one simulation model, limits the generalization of the results. The possibility that the simulation model is not totally realistic exists, due to the model's normality assumptions. Practical implications – Margin of error in input data estimation causes a significant risk of not achieving the required service level. It is proposed that managers work to improve the preciseness of the data, while the sensitivity analysis against statistical uncertainty, and a correction mechanism if necessary, should be integrated into optimization models. Originality/value – The output limitations in the optimization, i.e. service level, are typically stated precisely, but the capabilities of the input data have not been addressed adequately. This study provides valuable insights into ensuring the availability of critical materials.

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“…However, there exist such situations in which more than one supplier is necessary to reduce the total system cost or to sustain a desired service standard. Multi-supplier strategies can create a suppliers competition and ensure their providing faster delivery, see, e.g., [5]. The models considered below can be applied to logistics in agriculture or fuel supply in countries with continental climate.…”

Section: Introductionmentioning

confidence: 99%

Multi-supplier Systems with Seasonal Demand

Bulinskaya

Afanasyeva

2010

IFIP Advances in Information and Communication Technology

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Abstract. Multi-supplier inventory systems with seasonal demand are investigated via queuing theory methods in the framework of cost approach. Optimal distribution of replenishment orders between suppliers is obtained under assumption of make-to-order strategy. To this end asymptotic analysis of systems behavior is performed. We apply various mathematical tools such as weak convergence and use properties of regenerative, doubly stochastic Poisson and Markov processes.

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Inventory control in case of unknown demand distribution

Cited by 12 publications

References 1 publication

Cost and Reliability Approaches in Inventory Theory

Cost and Reliability Approaches in Inventory Theory

Exploring incomplete information in maintenance materials inventory optimization

Multi-supplier Systems with Seasonal Demand

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