scholarly journals Stochastic Inventory Model for Minimizing Blood Shortage and Outdating in a Blood Supply Chain under Supply and Demand Uncertainty

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Han Shih ◽  
Suchithra Rajendran
Keyword(s):  
Supply Chain ◽  
Blood Supply ◽  
Demand Uncertainty ◽  
Supply And Demand ◽  
Chain Model ◽  
Supply Uncertainty ◽  
Demand And Supply ◽  
Blood Supply Chain ◽  
Supply Chain Model ◽  
Inventory Holding

Purpose. Blood, like fresh produce, is a perishable element, with platelets having a limited lifetime of five days and red blood cells lasting 42 days. To manage the blood supply chain more effectively under demand and supply uncertainty, it is of considerable importance to developing a practical blood supply chain model. This paper proposed an essential blood supply chain model under demand and supply uncertainty. Methods. This study focused on how to manage the blood supply chain under demand and supply uncertainty effectively. A stochastic mixed-integer linear programming (MILP) model for the blood supply chain is proposed. Furthermore, this study conducted a sensitivity analysis to examine the impacts of the coefficient of demand and supply variation and the cost parameters on the average total cost and the performance measures (units of shortage, outdated units, inventory holding units, and purchased units) for both the blood center and hospitals. Results. Based on the results, the hospitals and the blood center can choose the optimal ordering policy that works best for them. From the results, we observed that when the coefficient of demand and supply variation is increased, the expected supply chain cost increased with more outdating units, shortages units, and holding units due to the impacts of supply and demand fluctuation. Variation in the inventory holding and expiration costs has an insignificant effect on the total cost. Conclusions. The model developed in this paper can assist managers and pathologists at the blood donation centers and hospitals to determine the most efficient inventory policy with a minimum cost based on the uncertainty of blood supply and demand. The model also performs as a decision support system to help health care professionals manage and control blood inventory more effectively under blood supply and demand uncertainty, thus reducing shortage of blood and expired wastage of blood.

An Empirical Comparison of Anticipatory and Response‐Based Supply Chain Strategies

1998 ◽  
Vol 9 (2) ◽  
pp. 21-34 ◽  
Author(s):  
David J. Closs ◽  
Anthony S. Roath ◽  
Thomas J. Goldsby ◽  
James A. Eckert ◽  
Stephen M. Swartz
Keyword(s):  
Supply Chain ◽  
Customer Service ◽  
Information Exchange ◽  
Demand Uncertainty ◽  
Chain Model ◽  
Performance Impact ◽  
Simulation Research ◽  
Supply Chain Model ◽  
Demand Variation ◽  
And Performance

This paper reports simulation research that empirically investigates and compares supply chain performance under varying conditions of information exchange and demand uncertainty. Specifically, the research objective is to quantitatively document the characteristics and performance impact of information exchange among supply chain entities. The findings suggest that the response‐based supply chain model consistently outperforms the anticipatory model in terms of customer service delivered under conditions of both low and high demand variation. Comparisons of inventory holdings across supply chain models demonstrate that the retailers' inventory burden is significantly lower in the response‐based scenario. The inventory savings enjoyed by retailers in the response‐based model are substantial enough to lower system‐wide inventories. In sum, the study supports the feasibility of achieving both improved service and lower inventories as a result of information sharing.

scholarly journals Optimal ordering policy in a two-echelon supply chain model with variable backorder and demand uncertainty

2020 ◽  
Author(s):  
Sumon Sarkar ◽  
B. C. Giri
Keyword(s):  
Supply Chain ◽  
Lead Time ◽  
Demand Uncertainty ◽  
Trade Credit ◽  
Chain Model ◽  
Order Quantity ◽  
Optimal Decisions ◽  
Solution Algorithms ◽  
Supply Chain Model ◽  
Credit Financing

The paper investigates a two-echelon production-delivery supply chain model for products with stochastic demand and backorder-lost sales mixture under trade-credit financing. The manufacturer delivers the retailer's order quantity in a number of equal-sized shipments. The replenishment lead-time is such that it can be crashed to a minimum duration at an additional cost that can be treated as an investment. Shortages in the retailer's inventory are allowed to occur and are partially backlogged with a backlogging rate dependent on customer's waiting time. Moreover, the manufacturer offers the retailer a credit period which is less than the reorder interval. The model is formulated to find the optimal solutions for order quantity, safety factor, lead time, and the number of shipments from the manufacturer to the retailer in light of both distribution-free and known distribution functions. Two solution algorithms are provided to obtain the optimal decisions for the integrated system. The effects of controllable lead time, backorder rate and trade-credit financing on optimal decisions are illustrated through numerical examples.

scholarly journals Blood Supply Chain Risk Management using House of Risk Model

2018 ◽  
Vol 16 (8) ◽  
pp. 573-591
Author(s):  
Wijai BOONYANUSITH ◽  
Phongchai JITTAMAI
Keyword(s):  
Risk Management ◽  
Supply Chain ◽  
Information Sharing ◽  
Blood Supply ◽  
Supply Chain Risk Management ◽  
Supply Chain Risk ◽  
Demand And Supply ◽  
Management Actions ◽  
Blood Supply Chain

Managing blood supply chain has been an important task in the healthcare system because it has to confront not only blood demand and supply uncertainties but also complexities in blood inventory management. In order to overcome these challenges, it is essential to explore the possible risks that could occur in the blood supply chain and discover proper ways to manage these risks. Therefore, this research aims to investigate risks in blood supply chain by using a proactive risk management tool called ‘house of risk’ (HOR) model, in order to conduct risk assessment and evaluate risk management actions. A case study of blood supply chain risk management was analyzed, and the HOR model was incorporated to appraise the appropriate actions in the real situation. The results indicate that there are 30 risk events and 16 risk agents identified and assessed in the case study. The outcomes point out that lack of collaboration, insufficient information for decision-making, and limited information sharing are the top 3 risk agents that contribute to significant impact on blood supply chain management. Risk mitigation and management actions were evaluated and the results show that enhancing the collaboration is the most proactive action to manage risks in the blood service operations, followed by information sharing, and demand and supply statistical analysis. The study has recommended the outlines for improving collaboration between blood service organizations by using information system and technology to mitigate risks, complexities, as well as uncertainties in managing demand and supply in the blood supply chain.

scholarly journals Challenge and opportunity research in blood supply chain management: a literature review

2018 ◽  
Vol 154 ◽  
pp. 01092 ◽  
Author(s):  
Agus Mansur ◽  
Iwan Vanany ◽  
Niniet Indah Arvitrida
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Blood Supply ◽  
Supply And Demand ◽  
Future Research ◽  
Chain Management ◽  
Blood Supply Chain ◽  
Perishable Commodity ◽  
Production Inventory ◽  
Commodity Demand

An interconnected series of the blood management is called blood supply chain management (BSCM). The stages of BSCM consisted of blood collecting, production, inventory, and distribution. The main challenges in BSCM are related to shortage, outdate, and supply chain cost which needed to minimize. Naturally, problems in BSCM are complex, it is not an easy task to find the solution. This complexity brought by several factors as follows: its inflicted risk, the uncertainty of supply and demand, blood nature as perishable commodity, demand uniqueness, and cost occurred. This research purposes was to review of various research related to BSCM and highlight opportunities to develop further research in blood supply chain (BSC). The result of this research is a suggestion on various possible future research to be explored in BSC, for example, developing an adaptive inventory model to support blood supply chain management that could be responsive toward demand fluctuation and developing collecting strategy to minimize shortage, outdate and incurred cost in supply chain level.

Information Sharing in Supply Chain Management with Demand Uncertainty

2011 ◽  
pp. 44-62 ◽  
Author(s):  
Zhensen Huang ◽  
Aryya Gangopadhyay
Keyword(s):  
Supply Chain ◽  
Information Sharing ◽  
Demand Uncertainty ◽  
Bullwhip Effect ◽  
Supply Chain Performance ◽  
Chain Model ◽  
Simulation Approach ◽  
Supply Chain Model ◽  
Trading Partners ◽  
The Impact

Information sharing is a major strategy to counteract the amplification of demand fluctuation going up the supply chain, known as the bullwhip effect. However, sharing information through interorganizational channels can raise concerns for business management from both technical and commercial perspectives. The existing literature focuses on examining the value of information sharing in specific problem environments with somewhat simplified supply chain models. The present study takes a simulation approach in investigating the impact of information sharing among trading partners on supply chain performance in a comprehensive supply chain model that consists of multiple stages of trading partners and multiple players at each stage.

Three-Layer Supply Chain Production/By-Production Inventory Model Under Fuzzy Rough Environment

2018 ◽  
Vol 17 (01) ◽  
pp. 61-88
Author(s):  
Prasanta Kr Ghosh ◽  
Samar Hazari ◽  
Jayanta Kumar Dey ◽  
Samarjit Kar
Keyword(s):  
Supply Chain ◽  
Raw Materials ◽  
Chain Model ◽  
Holding Costs ◽  
Setup Costs ◽  
Decision Variables ◽  
Constant Rate ◽  
Supply Chain Model ◽  
Production Inventory ◽  
Inventory Holding

An integrated three-layer supply chain model for production and by-production system is formulated under fuzzy-rough (Fu-Ro)-environment. At first, supplier receives the deteriorating items in a lot and supplies the fresh units to manufacturer for production. Manufacturer has two plants: plant-1 and plant-2. Manufacturer purchases these fresh raw materials at a constant rate from supplier to produce the main product in plant-1. Retailer-I has purchased this product from manufacturer of plant-1 to sale to the customers. The residue units of plant-1 have transferred to plant-2 with constant rate to manufacture another usable by-product. Retailer-II purchases this usable by-product and sales to the customers. Ideal costs of supplier, manufacturer and retailer have been taken into account. By-production of residue units of plant-1 not only minimizes the environmental pollution, but also gives some return to the manufacturer. Due to the complexity of environment, inventory holding costs, idle costs and setup costs are considered as Fu-Ro type and these are reduced to crisp ones using Fu-Ro expectation. Supply rate, production and by-production rates are assumed as decision variables. Integrated model has been developed and solved analytically in crisp and Fu-Ro environments to find the optimum value of the decision variables and corresponding individual profits of the members of the supply chain are calculated numerically and graphically. Finally, the model has been realized with a case study of sugar mill.

scholarly journals Dynamic Stochastic Optimization of Emergent Blood Collection and Distribution from Supply Chain Perspective

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Xiangyu Jin ◽  
Huajun Tang ◽  
Yuxin Huang
Keyword(s):  
Supply Chain ◽  
Blood Supply ◽  
Blood Donors ◽  
Blood Donation ◽  
Blood Collection ◽  
Chain Model ◽  
Blood Supply Chain ◽  
Conduct Sensitivity Analysis ◽  
Managerial Implications ◽  
Dynamic Stochastic

In response to emergencies, it is critical to investigate how to deliver emergency supplies efficiently and securely to disaster-affected areas and people. There is no doubt that blood is deemed one of the vital relief supplies, and ensuring smooth blood delivery may substantially alleviate subsequent impacts caused by the disaster. Taking red blood cell products as the research object, this work proposes a four-echelon blood supply chain model. Specifically, it includes blood donors, blood donation houses, blood centres, and hospitals. Furthermore, numerical analysis is provided to test the feasibility of blood collection and distribution schemes and conduct sensitivity analysis to test the impacts of the relevant parameters (e.g., apheresis donation proportion of red blood cells (RBCs), distance between blood donors and blood facilities, and times of blood donation) on the scheme. This research provides some scientific and reasonable support for decision makers and managerial implications for emergency departments and contributes to the study of emergent blood supply chain.

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