Technical note: Some structural results on acyclic supply chains

Shi, Jim; Zhao, Yue

doi:10.1002/nav.20421

Cited by 8 publications

(4 citation statements)

References 13 publications

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“…For general supply chain networks, Lesnaia (2004) shows that the problem is NP-hard. Magnanti et al (2006), Shu and Karimi (2009), Shi and Zhao (2010) and Li and Jiang (2012) propose several efficient heuristic algorithms and analyse the structural properties for the general acyclic network problem.…”

Section: Literature Reviewmentioning

confidence: 99%

Trade-off between service time and carbon emissions for safety stock placement in multi-echelon supply chains

2015

International Journal of Production Research

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With the low-carbon revolution, many firms face the continuous challenge for reducing carbon emissions in their supply chain activities. Built upon the strategic safety stock placement model, in this paper, we model the carbon emissions for each stage of a multi-echelon supply chain as a function of the service time guaranteed by this stage to its immediate downstream stages. We establish that there is a negative correlation between service time and carbon emissions at each stage. Based on this, we develop two models to study the trade-off between service time and carbon emissions for safety stock placement in multi-echelon supply chains by considering carbon cap and carbon tax, respectively. Both of them are solved using iterative piecewise linear approximations. We implement these two models to study how carbon cap, carbon emission cost rate and guaranteed service time affect the optimal safety stock placement using a real chain.

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Section: Literature Reviewmentioning

confidence: 99%

Trade-off between service time and carbon emissions for safety stock placement in multi-echelon supply chains

2015

International Journal of Production Research

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“…Unlike the abovementioned studies, this paper integrates the surgery durations and LOS in the ICU as the overall surgery duration, and also takes LOS into consideration. In principle, risk and uncertainty is a primary consideration in the broad context of operations management; readers are referred to Shi and Zhao ( 2010 ), Shi Katehakis, and Melamed ( 2013 ), Shi, Katehakis, et al ( 2014 ), Shi, Yue, et al ( 2014 ), Shi et al ( 2019 )), Chang et al ( 2019 ), Katehakis et al, ( 2015 , 2016 ), Shi ( 2016 ), Xiao and Shi ( 2016 ), Qi, et al ( 2015 ), Chang and Shi ( 2017 ), among many others.…”

Section: Literature Reviewmentioning

confidence: 99%

Surgical scheduling by Fuzzy model considering inpatient beds shortage under uncertain surgery durations

et al. 2022

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Operating Room (OR) management has been among the mainstream of hospital management research, as ORs are commonly considered as one of the most critical and expensive resources. The complicated connection and interplay between ORs and their upstream and downstream units has recently attracted research attention to focus more on allocating medical resources efficiently for the sake of a balanced coordination. As a critical step, surgical scheduling in the presence of uncertain surgery durations is pivotal but rather challenging since a patient cannot be hospitalized if a recovery bed will not be available to accommodate the admission. To tackle the challenge, we propose an overflow strategy that allows patients to be assigned to an undesignated department if the designated one is full. It has been proved that overflow strategy can successfully alleviate the imbalance of capacity utilization. However, some studies indicate that implementation of the overflow strategy exacerbates the readmission rate as well as the length of stay (LOS). To rigorously examine the overflow strategy and explore its optimal solution, we propose a Fuzzy model for surgical scheduling by explicitly considering downstream shortage, as well as the uncertainty of surgery duration and patient LOS. To solve the Fuzzy model, a hybrid algorithm (so-called GA-P) is developed, stemming from Genetic Algorithm (GA). Extensive numerical results demonstrate the plausible efficiency of the GA-P algorithm, especially for large-scale scheduling problems (e.g., comprehensive hospitals). Additionally, it is shown that the overflow cost plays a critical role in determining the efficiency of the overflow strategy; viz., benefits from the overflow strategy can be reduced as the overflow cost increases, and eventually almost vanishes when the cost becomes sufficiently large. Finally, the Fuzzy model is tested to be effective in terms of simplicity and reliability, yet without cannibalizing the patient admission rate.

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“…Their engagement has resulted in several papers, (c.f., (Bar-Lev et al, 2009;2017;2017a;2017b;Bar-Lev and Perry, 1989;Bar-Lev et al, 2005;2007;2013;. Other works can be found in (Abolnikov and Dukhovny, 2003;Kopach et al, 2008;Beliën and Forcé, 2012;Civelek et al, 2015;Ghandforoush and Sen, 2010;Karaesmen et al, 2011;Marshall et al, 2004;Sebastian et al, 2012;Shi and Zhao, 2010;Deniz et al, 2010;Blake and Hardy, 2014;Xie et al, 2012). The aim in those paper was to develop comprehensive inventory control and group testing models that incorporate the key features of a CBS and a hospital blood bank.…”

Section: Some Research Work Related To the Stochastic Approachmentioning

confidence: 99%

A Stochastic Approach to Blood Supply, Demand and Screening in Central Blood Banks - A Review

Bar‐Lev¹

2017

Current Research in Biostatistics

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Abstract:One of the major issues in securing blood supply to patients worldwide is to provide blood of the best achievable quality, in the needed quantities. Central Blood Services (CBS's) worldwide are daily faced with the problem how to satisfy demands for blood from various hospitals. These hospitals, in their turn, are faced with the problem how to satisfy demands for blood from their patients. To solve these problems in a costeffective way is notoriously difficult, because (i) the amounts of available blood and of blood demand are random, (ii) blood can only be used during a limited amount of time, (iii) one must distinguish various blood components (red blood cells, plasma and platelets) with different associated costs and perishability and (iv) one must distinguish persons with different blood types (like AB + and O − ) with different capabilities to act as donor or as recipient. In this review paper we provide the subject background, describing the blood characteristics and the operation of CBS and hospital blood banks. In particular we describe blood demand, blood components and blood types. We depict blood screening procedures and their processing times and provide with some real data. Particularly we describe a stochastic approach to blood screening and inventory. An emphasis will be given to inventory management and blood allocation, stochastic imput-output of the inventory system and some cost functions involved.

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Technical note: Some structural results on acyclic supply chains

Cited by 8 publications

References 13 publications

Trade-off between service time and carbon emissions for safety stock placement in multi-echelon supply chains

Trade-off between service time and carbon emissions for safety stock placement in multi-echelon supply chains

Surgical scheduling by Fuzzy model considering inpatient beds shortage under uncertain surgery durations

A Stochastic Approach to Blood Supply, Demand and Screening in Central Blood Banks - A Review

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