A network flow model for inventory management and distribution of influenza vaccines through a healthcare supply chain

Hovav, Sharon; Tsadikovich, Dmitry

doi:10.1016/j.orhc.2015.05.003

Cited by 70 publications

(38 citation statements)

References 26 publications

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“…In the same year, Mestre et al [31] presented two hierarchical location-allocation models with a demand under uncertainty to enhance the geographic access while minimizing the costs in the hospital network. Also, Hovav and Tsadikovich [32] proposed a facility location inventory problem to reduce the cost of the influenza vaccination program. Elalouf et al [33] to reduce operating costs by repairing and maintaining blood sample collection chain have developed a model for facility location problem solving and proposed the dynamic programming (DP) algorithm and fully polynomial time approximation scheme (FPTAS) algorithm to solve it.…”

Section: Hierarchical Location-allocation For Supply Chains Ofmentioning

confidence: 99%

Five-Echelon Multiobjective Health Services Supply Chain Modeling under Disruption

Gargari

Sayad

Mashhadi

et al. 2021

Mathematical Problems in Engineering

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Medicine unreliability problem is taken into consideration as one of the most important issues in health supply chain management. This research is associated with the development of a multiobjective optimization problem for the selection of suppliers and distributors. To achieve the purposes, the optimal quota allocation is determined with respect to disruption of suppliers in a five-echelon supply chain network and consideration of the distributor centers as a hub location-allocation mode. The objective of the optimization model is involved in simultaneous minimization of transactions costs dealing with suppliers, expected purchasing costs from suppliers, expected percentages of delayed and returned products in each distributor, as well as transportation cost in each echelon and fixed cost for distributor centers, and finally maximization of the expected scores for suppliers and high priority of product customers. The optimization problem is formulated as a mixed-integer nonlinear programming model. The proposed optimization model is utilized to investigate a numerical case study for asthma-specific medicines. The analyzing procedure is conducted based on the collected real data from Cobel Darou pharmaceutical company in 2019. Furthermore, a fuzzy multichoice goal programming model is considered to solve the proposed optimization model by R optimization solver. The numerical results confirmed the authenticity of the model.

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Section: Hierarchical Location-allocation For Supply Chains Ofmentioning

confidence: 99%

Five-Echelon Multiobjective Health Services Supply Chain Modeling under Disruption

Gargari

Sayad

Mashhadi

et al. 2021

Mathematical Problems in Engineering

View full text Add to dashboard Cite

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“…(Duintjer Tebbens et al, 2010) developed a mathematical model for determining the optimal management of vaccine stockpile. Hovav and Tsadikovich (2015) developed a network flow model for inventory management and distribution of influenza vaccines through a supply chain. Mofrad et al (2014) formulated a Markov decision process model that addresses the issue of open-vial wastage.…”

Section: Literature Reviewmentioning

confidence: 99%

Prioritizing the vaccine supply chain issues of developing countries using an integrated ISM-fuzzy ANP framework

Chandra

Kumar

2019

JM2

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Purpose Delivering vaccines to the children who need them requires a supply chain that is efficient and effective. In most of the developing countries, however, the unknown and unresolved supply chain issues are causing inefficiencies in distributing vaccines. There is, therefore, a great need in such countries to recognize the issues that cause delays in vaccine delivery. With this purpose, the present study aims to identify and analyze the key issues in the supply chain of basic vaccines required to immunize children in developing countries. Design/methodology/approach Based on a field survey of three states of India, in-depth review of relevant literature and experts’ opinions, 25 key issues were recognized as factors of the vaccine supply chain (VSC) and categorized into five main domains. Using integrated interpretive structural modeling and fuzzy analytic network process approaches, the issues have been prioritized to determine their relative importance in the VSC. In addition, a sensitivity analysis has been performed to investigate the priority stability of the issues. Findings The results of the analysis show that among the five domains of VSC issues, the economic domain with a weight of 0.4262 is the most important domain, followed by the management (0.2672), operational (0.2222), environmental (0.0532) and social (0.0312). Research limitations/implications This study focuses on the prioritization of VSC issues; therefore, the results of the present study can provide direction to the decision-makers of immunization programs of developing countries in driving their efforts and resources on eliminating the most important obstacles to design successful vaccination programs. Originality/value To the authors’ knowledge, this paper is first to provide a direction to the decision-makers in identifying and managing important issues through the use of an analytical approach.

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“…They found operations researchers heavily concentrate on the strategic decisions in vaccine distribution chains and, to a lesser extent, tactical and operational decisions. Hovav and Tsadikovich ( 2015 ) used mathematical programming and proposed an optimization model to design a healthcare supply chain to control influenza vaccines’ distribution and inventory control. Saif and Elhedhli ( 2016 ) developed a cold supply chain for the distribution and inventory management of vaccines considering environmental issues.…”

Section: Introductionmentioning

confidence: 99%

A mathematical programming approach for equitable COVID-19 vaccine distribution in developing countries

et al. 2021

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Developing countries scramble to contain and mitigate the spread of coronavirus disease 2019 (COVID-19), and world leaders demand equitable distribution of vaccines to trigger economic recovery. Although numerous strategies, including education, quarantine, and immunization, have been used to control COVID-19, the best method to curb this disease is vaccination. Due to the high demand for COVID 19 vaccine, developing countries must carefully identify and prioritize vulnerable populations and rationalize the vaccine allocation process. This study presents a mixed-integer linear programming model for equitable COVID-19 vaccine distribution in developing countries. Vaccines are grouped into cold, very cold, and ultra-cold categories where specific refrigeration is required for their storage and distribution. The possibility of storage for future periods, facing a shortage, budgetary considerations, manufacturer selection, order allocation, time-dependent capacities, and grouping of the heterogeneous population are among the practical assumptions in the proposed approach. Real-world data is used to demonstrate the efficiency and effectiveness of the mathematical programming approach proposed in this study.

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A network flow model for inventory management and distribution of influenza vaccines through a healthcare supply chain

Cited by 70 publications

References 26 publications

Five-Echelon Multiobjective Health Services Supply Chain Modeling under Disruption

Five-Echelon Multiobjective Health Services Supply Chain Modeling under Disruption

Prioritizing the vaccine supply chain issues of developing countries using an integrated ISM-fuzzy ANP framework

A mathematical programming approach for equitable COVID-19 vaccine distribution in developing countries

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