Newsvendor decisions under supply uncertainty

Käki, Anssi; Liesiö, Juuso; Salo, Ahti; Talluri, Srinivas

doi:10.1080/00207543.2014.952798

Cited by 36 publications

(23 citation statements)

References 33 publications

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“…Due to its rare, scarce, and perishable nature, human blood and its byproducts require special inventory management models to be used at the blood banks in BSCs. Besides, giving a detailed portrayal of how BSCs operate, our supply aggregation model for blood types may be incorporated in single-period (perishable) inventory management models with supply uncertainty (cf., Käki et al, 2015) and also in developing operating characteristics for continuous review systems for perishables (e.g., Tekin et al, 2001). Furthermore, our model can feed into the current literature in which generally incorporates only demand stochasticity in BSC network optimization such as in , and in Jabbarzadeh et al (2014).…”

Section: Discussionmentioning

confidence: 99%

Vein to vein: exploring blood supply chains in Canada

Maeng

Sabharwal

Ülkü

2018

JOSCM

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<p class="Keywords">There is not yet any substitute for human blood which remains a scarce resource in many countries. Effective and efficient management of blood supply chains (BSCs) is utmost important in the healthcare industry. This paper gives an overview of the BSC and how blood products are used at hospitals to provide life-saving services to patients. Factoring in the blood types and their receipt compatibility, a simple inventory model is proposed. Using secondary data, the model is illustrated by way of a small case study in Nova Scotia, Canada. We highlight that due to both demand and supply uncertainties, and due to its perishable nature, inventorying blood products is not straightforward and brings with it many logistical and management challenges in the BSC.</p>

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Section: Discussionmentioning

confidence: 99%

Vein to vein: exploring blood supply chains in Canada

Maeng

Sabharwal

Ülkü

2018

JOSCM

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“…We present the encouraging out-of-sample performance of our data-driven minimax regret model over alternative data-driven models based on Hurwicz decision criterion and its variants (Section 6.1), over a minimax regret model in Perakis and Roels (2008) that is based on partial statistical information on moments (Section 6.2), and in a test where the testing distribution differs from the training one (Section 6.3). Throughout these experiments, we use the same parameters as Schweitzer and Cachon (2000) and Käki et al (2015): the unit price is p = 12, while the unit cost may take c = 3…”

Section: Numerical Experimentsmentioning

confidence: 99%

“…Here, a ū−u ¯, b v −v ¯, and η represents dependency strength; in other words, the linear correlation coefficient of ũ and ṽ is η/3. In fact, independent demand and yield may not always be realistic: they are negatively correlated if the supply capacity is constrained while being positively correlated if suppliers can flexibly increase the capacity (see detailed motivating examples in Käki et al 2015).…”

Section: Comparisons Of Decision Criteria With Both Demand and Yield Randomnessmentioning

confidence: 99%

Regret in the Newsvendor Model with Demand and Yield Randomness

Chen

Xie

2020

SSRN Journal

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We study the fundamental stochastic newsvendor model that considers both demand and yield randomness.It is usually difficult in practice to describe precisely the joint demand and yield distribution, although partial statistical information and empirical data about this ambiguous distribution are often accessible. We combat the issue of distributional ambiguity by taking a data-driven distributionally robust optimization approach to hedge against all distributions that are sufficiently close to a uniform and discrete distribution of empirical data, where closeness is measured by the type-∞ Wasserstein distance. We adopt the minimax regret decision criterion to assess the optimal order quantity that minimizes the worst-case regret. Several properties about the minimax regret model, including optimality condition, regret bound, and the worst-case distribution, are presented. The optimal order quantity can be determined via an efficient golden section search. We extend the analysis to the Hurwicz criterion model, which generalizes the popular albeit pessimistic maximin model (maximizing the worst-case expected profit) and its (less noticeable) more optimistic counterpart-the maximax model (maximizing the best-case expected profit). Finally, we present numerical comparisons of our data-driven minimax regret model with data-driven models based on the Hurwicz criterion and with a minimax regret model based on partial statistical information on moments.

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“…Many extensions have been proposed in the last decades. Worth to mention the work of [25], in which re-ordering opportunities are permitted in a two-period problem, and the one of [26] which considers a newsvendor model with uncertain demand and supply. Recently, few works have begun to introduce inventory theory models applied to energy storage.…”

Section: Inventory Models With Energy Considerationsmentioning

confidence: 99%

Multi-Period Newsvendor Problem for the Management of Battery Energy Storage Systems in Support of Distributed Generation

2019

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Stakeholders’ interests on renewable and clean energy sources experienced a huge increase in the last decades, thanks to the remarkable benefits on climate, economic, and social issues. The integration of flexible energy storage systems represents a great chance for a further increased penetration as they support the mitigation of renewables’ main drawbacks (i.e., stochastic behavior) and guarantee the balance between energy supply and demand enabling non-simultaneous production and consumption. The increased focus on distributed generation and storage was also of interest to the research community which investigated both the economic and technical performances of the integrated systems. The operations management branch addressed this topic, since storage devices present many similarities with traditional inventory management applied to regular commodities. At a user level, the relation between energy production and storage can be studied by analogy with inventory models. Specifically, this study presents a multi-period newsvendor model for the management and optimal sizing of a battery energy storage system installed to increase the self-consumption rate by allowing loads shifting. This work aims to extend the traditional inventory management applying its concepts to energy systems operations in order to minimize the total energy cost. A numerical study is provided to show the behavior of the model.

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Newsvendor decisions under supply uncertainty

Cited by 36 publications

References 33 publications

Vein to vein: exploring blood supply chains in Canada

Vein to vein: exploring blood supply chains in Canada

Regret in the Newsvendor Model with Demand and Yield Randomness

Multi-Period Newsvendor Problem for the Management of Battery Energy Storage Systems in Support of Distributed Generation

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