Multiple Lotsizing in Production to Order with Random Yields: Review of Recent Advances

Grosfeld-Nir, Abraham; Gerchak, Yigal

doi:10.1023/b:anor.0000012275.01260.f5

Cited by 146 publications

(59 citation statements)

References 34 publications

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“…The supply uncertainty in our model has a binomial structure, a more appropriate choice in personnel staffing settings. Binomial yield models are a relative rarity in the stochastic yield literature, perhaps due to their limited analytical tractability (Gerchak and Henig (1994), Grosfeld-Nir and Gerchak (2004), Fadiloglu et al (2008)). Most importantly, our analysis is the first one to introduce and analyze endogenous stochastic yields.…”

Section: Introduction and Literature Reviewmentioning

confidence: 99%

“Nursevendor Problem”: Personnel Staffing in the Presence of Endogenous Absenteeism

2013

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The problem of determining nurse staffing levels in a hospital environment is a complex task due to variable patient census levels and uncertain service capacity caused by nurse absenteeism. In this paper we combine an empirical investigation of the factors affecting nurse absenteeism rates with an analytical treatment of nurse staffing decisions using a novel variant of the newsvendor model. Using data from the emergency department of a large urban hospital, we find that absenteeism rates are consistent with nurses exhibiting an aversion to higher levels of anticipated workload. Using our empirical findings we analyze a single-period nurse staffing problem considering both the case of constant absenteeism rate (exogenous absenteeism) as well as an absenteeism rate which is a function of the number of scheduled nurses (endogenous absenteeism).We provide characterizations of the optimal staffing levels in both situations and show that the failure to incorporate absenteeism as an endogenous effect results in understaffing.

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Section: Introduction and Literature Reviewmentioning

confidence: 99%

“Nursevendor Problem”: Personnel Staffing in the Presence of Endogenous Absenteeism

2013

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“…The same holds for additional yield types mentioned in Yano and Lee (1995), like interrupted geometric yield or yield uncertainty from random capacity. Furthermore, it would be a challenging task to study how contracts can be used for supply chain coordination in planning environments with multiple productions runs that are addressed in Grosfeld-Nir and Gerchak (2004).…”

Section: Interaction Of Buyer and Suppliermentioning

confidence: 99%

“…Often, however, other yield types are found (see Yano and Lee 1995) which are of greater practical relevance and demand for specific consideration in decision making and contract analysis. Literature contributions which refer to a larger variety of yield models concentrate on planning situations where multiple production lots within a single period can be released [see (Grosfeld-Nir and Gerchak 2004) for an overview]. These studies, however, only address centralized decision making problems.…”

Section: Introductionmentioning

confidence: 99%

Supply chain coordination by contracts under binomial production yield

Clemens

Inderfurth

2015

Bus Res

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Supply chain coordination is enabled by adequately designed contracts so that decision making by multiple actors avoids efficiency losses in the supply chain. From the literature it is known that in newsvendor-type settings with random demand and deterministic supply the activities in supply chains can be coordinated by sophisticated contracts while the simple wholesale price contract fails to achieve coordination due to the double marginalization effect. Advanced contracts are typically characterized by risk sharing mechanisms between the actors, which have the potential to coordinate the supply chain. Regarding the opposite setting with random supply and deterministic demand, literature offers a considerably smaller spectrum of solution schemes. While contract types for the well-known stochastically proportional yield have been analyzed under different settings, other yield distributions have not received much attention in the literature so far. However, practice shows that yield types strongly depend on the industry and the production process that is considered. As consequence, they can deviate very much from the specific case of a stochastically proportional yield. This paper analyzes a buyersupplier supply chain in a random yield, deterministic demand setting with production yield of a binomial type. It is shown how under binomially distributed yields risk sharing contracts can be used to coordinate buyer's ordering and supplier's production decision. Both parties are exposed to risks of overproduction and under-delivery. In contrast to settings with stochastically proportional yield, however, the impact of yield uncertainty can be quite different in the binomial yield case. Under binomial yield, the output uncertainty decreases with larger production quantities while it is independent from lot sizes under stochastically proportional yield. Consequently, the results from previous contract analyses on other yield types 123Business Research (2015) 8:301-332 DOI 10.1007 may not hold any longer. The current analytical study reveals that, like under stochastically proportional yield, coordination is impeded by double marginalization if a simple wholesale price contract is applied. However, more sophisticated contracts which penalize or reward the supplier can change the risk distribution so that supply chain coordination is possible also under binomial yield. In this context, many contract properties from planning under stochastically proportional yield carry over. Nevertheless, numerical examples reveal that a misspecification of the yield type can considerably downgrade the extent of supply chain coordination.

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“…Hence, such a process can only be analyzed thoroughly when both processes disassembly and rework are evaluated separately. Considering stochastic yields has attained significant interest in the scientific literature as the basic work of Yano and Lee [16] as well as the overview of Grosfeld-Nir and Gerchak [17] present. However, most of the contributions mentioned in [17] describe purely manufacturing environments which cannot be entirely translated to a remanufacturing system as this inherits greater risks to be dealt with [18].…”

Section: Introductionmentioning

confidence: 99%

On the alignment of lot sizing decisions in a remanufacturing system in the presence of random yield

Schulz

Ferretti

2011

Jnl Remanufactur

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Multiple Lotsizing in Production to Order with Random Yields: Review of Recent Advances

Cited by 146 publications

References 34 publications

“Nursevendor Problem”: Personnel Staffing in the Presence of Endogenous Absenteeism

“Nursevendor Problem”: Personnel Staffing in the Presence of Endogenous Absenteeism

Supply chain coordination by contracts under binomial production yield

On the alignment of lot sizing decisions in a remanufacturing system in the presence of random yield

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