An inter-temporal resource emergency management model

Qin, Junchang; Xing, Yiting; Wang, Song; Wang, Kanliang; Chaudhry, Sohail S.

doi:10.1016/j.cor.2011.07.008

Cited by 15 publications

(6 citation statements)

References 27 publications

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“…Emergency resources can be classified as those consumed during the response period and those that are consumed during the recovery period. Qin et al [ 6 ] proposed an inter-temporal integrated single-period resource model for solving the optimal order quantity that meets the needs that arise during the recovery period. Balcik et al [ 7 ] presented a literature review on inventory management in humanitarian supply chains.…”

Section: Literature Reviewmentioning

confidence: 99%

Prepositioning Emergency Inventories Under Uncertainties of Time, Location, and Quantity

Keren

2023

Oper. Res. Forum

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An emergency incident will occur in the coming years, somewhere. It will be an earthquake, a landslide, a volcanic eruption, an epidemic of infectious disease, or some other disaster. Positioning an emergency or humanitarian inventory in advance is a response that can greatly mitigate the effects of the expected incident. However, the problem is to put the emergency inventory in the right location to use the right quantity and to do so at the right time—taking into account that the location, timing, and magnitude of the incident may be random variables. This paper presents a model for the triple uncertainty of the inventory problem (location, timing, and quantity) and shows how the solution can be optimized analytically and numerically, even in cases where there is a statistical dependence between the random variables. An important contribution of the paper is the addition of the dimension of timing to the inventory problem. One result of the model can be an immediate establishment of an emergency inventory with the optimal quantity and location of materials, another can be a “wait and see” strategy with periodic updating of the model as newer information becomes available. The paper provides benchmark solutions that can help decision-makers make wiser choices about the timing, location, and quantity of inventories positioned in anticipation of an emergency incident. The model is useful especially for disasters with a long mean time between occurrences (years), which motivate decision-makers to adopt the wait and see strategy.

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Section: Literature Reviewmentioning

confidence: 99%

Prepositioning Emergency Inventories Under Uncertainties of Time, Location, and Quantity

Keren

2023

Oper. Res. Forum

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“…Second, only a single kind of resource is considered in this paper, but the fact is not like the case. The Emergency inventory system with many kinds of emergency resources need to be further studied [ 30 ]. Thirdly, the emergency or violate situation is full of uncertainty, such as capacity, lead-time, service rate, and so on.…”

Section: Conclusion and Limitationsmentioning

confidence: 99%

Medical resource inventory model for emergency preparation with uncertain demand and stochastic occurrence time under considering different risk preferences at the airport

et al. 2017

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With the high accident rate of civil aviation, medical resource inventory becomes more important for emergency management at the airport. Meanwhile, medical products usually are time-sensitive and short lifetime. Moreover, we find that the optimal medical resource inventory depends on multiple factors such as different risk preferences, the material shelf life and so on. Thus, it becomes very complex in a real-life environment. According to this situation, we construct medical resource inventory decision model for emergency preparation at the airport. Our model is formulated in such a way as to simultaneously consider uncertain demand, stochastic occurrence time and different risk preferences. For solving this problem, a new programming is developed. Finally, a numerical example is presented to illustrate the proposed method. The results show that it is effective for determining the optimal medical resource inventory for emergency preparation with uncertain demand and stochastic occurrence time under considering different risk preferences at the airport.

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“…In literature [13], based on the characteristics of rescue operational process in flood disaster management, Qin from Xi'an Jiaotong University in China mentioned that these necessary emergency materials can be classified into two categories, namely response resources (e.g. sandbags and protection network) and recovery resources (e.g.…”

Section: Relief Classification From Point View Of Academiamentioning

confidence: 99%

Review of Relief Demand Forecasting Problem in Emergency Logistic System

Zhao¹,

Cao²

2015

JSSM

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Demand forecasting on relief is the premise and basis of material allocation scheme in emergency logistic system. Reasonable demand forecasting method can facilitate relief distribution, thus avoiding the phenomenon that supply-demand imbalance and relief distribution delay. In this paper, relief will be categorized from point view of government and academia, to explain the relationship between relief categorization and demand forecasting. Then introduce the characteristics of relief-demand from several aspects, such as sudden, uncertainty, timeliness, and stage. Finally, this paper gives an overall conclusion on current development of relief demand forecasting method. And elaborate the application of case-based reasoning, information entropy theory, considering safety stock in the field of relief-demand forecasting in detail, to provide reference for relief distribution.

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An inter-temporal resource emergency management model

Cited by 15 publications

References 27 publications

Prepositioning Emergency Inventories Under Uncertainties of Time, Location, and Quantity

Prepositioning Emergency Inventories Under Uncertainties of Time, Location, and Quantity

Medical resource inventory model for emergency preparation with uncertain demand and stochastic occurrence time under considering different risk preferences at the airport

Review of Relief Demand Forecasting Problem in Emergency Logistic System

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