•The addition of flu could cripple the health care system during the COVID-19 pandemic.•Fears of coronavirus have intensified the shortage of flu vaccine in developing countries.•We present an ...optimization model for equitable flu vaccine distribution.•The model utilizes an equitable objective function to distribute vaccines to high-risk people.•We present a case study to exhibit efficacy and demonstrate the model’s applicability.
The addition of other respiratory illnesses such as flu could cripple the healthcare system during the coronavirus disease 2019 (COVID-19) pandemic. An annual seasonal influenza vaccine is the best way to help protect against flu. Fears of coronavirus have intensified the shortage of influenza shots in developing countries that hope to vaccinate many populations to reduce stress on their health services. We present an inventory-location mixed-integer linear programming model for equitable influenza vaccine distribution in developing countries during the pandemic. The proposed model utilizes an equitable objective function to distribute vaccines to critical healthcare providers and first responders, elderly, pregnant women, and those with underlying health conditions. We present a case study in a developing country to exhibit efficacy and demonstrate the optimization model’s applicability.
•Developed a practical decision support system for COVID-19 healthcare supply chain.•Grouped people and provided an independent classification method for each group.•Evaluated the efficiency of the ...proposed approach using real-world data.
The disasters caused by epidemic outbreaks is different from other disasters due to two specific features: their long-term disruption and their increasing propagation. Not controlling such disasters brings about severe disruptions in the supply chains and communities and, thereby, irreparable losses will come into play. Coronavirus disease 2019 (COVID-19) is one of these disasters that has caused severe disruptions across the world and in many supply chains, particularly in the healthcare supply chain. Therefore, this paper, for the first time, develops a practical decision support system based on physicians' knowledge and fuzzy inference system (FIS) in order to help with the demand management in the healthcare supply chain, to reduce stress in the community, to break down the COVID-19 propagation chain, and, generally, to mitigate the epidemic outbreaks for healthcare supply chain disruptions. This approach first divides community residents into four groups based on the risk level of their immune system (namely, very sensitive, sensitive, slightly sensitive, and normal) and by two indicators of age and pre-existing diseases (such as diabetes, heart problems, or high blood pressure). Then, these individuals are classified and are required to observe the regulations of their class. Finally, the efficiency of the proposed approach was measured in the real world using the information from four users and the results showed the effectiveness and accuracy of the proposed approach.
In this paper, a bi-objective mixed-integer linear programming model is formulated for designing a perishable pharmaceutical supply chain network under demand uncertainty. The objectives of the ...proposed model are to simultaneously minimize the total cost of the network and lost demand amount. The proposed model is multi-product and multi-period and includes simultaneous facilities location, vehicle routing, and inventory management; hence, it is considered an operational-strategic model. Procurement discounts, the lifetime of products, storing products for future periods, lost demand, and soft and hard time windows are the main assumptions of the proposed model. A novel hybrid approach, based on fuzzy theory, chance constrained programming, and goal programming approach, is developed for solving the proposed bi-objective model. The validity of the proposed model and developed solution approach is evaluated using data from Avonex, a prefilled syringe distribution chain serving 11 health centers in Tehran. The proposed model indicates that some lost sales exist, and to overcome the lost sales, the case company needs to invest a little more in addition to the initial investment of around 2 billion tomans. The results obtained from implementing the model and the sensitivity analysis, using real-world data, confirm the efficiency and validity of the proposed mathematical model and solution approach.
In the real world, there are complex decision‐making problems in which a variety of intertwined factors and hierarchical structures exist, and it is difficult or impossible to solve these problems ...using classical methods. The prioritization of circular economy (CE) adoption barriers is one such complex problem that cannot be solved using current classical methods. Hence, in this paper, for the first time, a new method, namely, FBWDS, is developed. FBWDS derives from the combination of fuzzy best–worst method (BWM), fuzzy decision‐making trial and evaluation laboratory (DEMATEL), and Supermatrix structure. This proposed method establishes weights of the intertwined factors in hierarchical networks under uncertainty; these weighted factors and their interdependencies are calculated using the fuzzy BWM and fuzzy DEMATEL techniques, respectively. In addition, the Supermatrix structure is applied to integrate the results of these two techniques. The proposed approach efficiency is evaluated in the field of the CE adoption barriers using data from a cable and wire industry in Iran. The results showed that “high setup costs,” “financial limitations,” and “absence of public awareness about CE” rank as the most challenging barriers, and “lack of standards for designing recycled products” and “absence of standard system to evaluate performance” are the least important barriers to CE adoption in the cable and wire industry.
Since the advent of blockchain technology (BT), extensive research has explored using this technology in non-financial cases. The healthcare industry is one of the non-financial sectors that BT has ...significantly impacted. In this paper, for the first time, barriers to implement BT-based platforms from a balanced scorecard perspective in the healthcare sector are introduced, and these barriers are prioritized using a structural approach based on the weighted influence non-linear gauge system. Unlike other structural models such as decision-making trial and evaluation laboratory (DEMATEL), in this approach, both strength and influence intensity of components are considered in the ranking process. The proposed approach is applied in networks that have a hierarchical structure and intertwined components. The performance of the proposed approach is evaluated using the ranking of BT-based platform adoption barriers in the healthcare industry in Iran. The results show that financial issues, security issues, lack of expertise and knowledge, and uncertain government policies are the most important barriers to BT adoption in the healthcare industry.
Designing and developing sustainable circular supply chain networks for electric vehicle (EV) lithium‐ion battery recycling and production requires complex environmental sustainability and economic ...viability assessment. EVs use a lot of data for battery management and delivering optimum performance, and the Internet of Things (IoT) plays a major role in managing this data. This study develops a bi‐objective mixed‐integer linear programming model for designing a sustainable circular supply chain to manage the manufacturing, remanufacturing, and distribution of EV lithium‐ion batteries under uncertainty using the IoT and big data. The proposed model simultaneously minimizes total costs and CO2 emissions and uses IoT to improve network performance and create a traceable and secure environment. A fuzzy multi‐objective method solves the bi‐objective optimization model under uncertainty, and a simulation algorithm examines the effectiveness of the proposed model through simulated problems.
The tourism and hospitality industry significantly impacts socio-economic development and cultural growth in developing countries. This study develops an integrated multicriteria decision-making and ...optimization model for partner selection in public-private partnership (PPP) projects in the hospitality industry. The proposed model uses a weighted influence non-linear gauge system to evaluate the partners. A multi-objective optimization model is then utilized to select a partner for each PPP project using a linear programming metric solution approach. A case study demonstrates the applicability of the proposed model in a PPP project in Iran to renovate and convert historic houses into hotels for the hospitality industry.
In recent decades, reverse logistics has garnered considerable attention since it recovers value of returning products, satisfies environmental requirements, and pays attention to customers’ rights. ...Suppliers, as the first layer of the supply chain network, pose a great impact on environmental pollution. Therefore, in this paper a hybrid approach of fuzzy analysis network process (FANP), fuzzy decision-making trial and evaluation laboratory (FDEMATEL), and multi-objective mixed-integer linear programming (MOMILP) models are developed for circular supplier selection and order allocation in a multi-product circular closed-loop supply chain (C-CLSC) considering multi-depot, capacitated green routing problem using heterogeneous vehicles. In this regard, a mathematical model concerning an inventory-location-routing problem is developed that minimises cost and shortage simultaneously and also deals with imposed uncertainties. A fuzzy solution approach is proposed to simultaneously incorporate uncertainty and to change the multi-objective model into a single-objective model. To motivate the practical aspect of the proposed model in real world applications, we applied the model to an automotive timing belt manufacturer. The obtained results indicate that the proposed model is cost efficient and environmentally friendly for CLSC network designs.
Circular supplier selection is the process of selecting suppliers in a closed-loop supply chain. Sustainable circular supplier selection addresses the social and environmental concerns in circular ...supplier selection problems. In this paper, for the first time, we combine the fuzzy best-worst method and the interval VIKOR technique to evaluate and prioritize sustainable suppliers in circular supply chains. The evaluation criteria are classified into three categories of economic, social, and circular factors extracted based on the domain expert's opinions. The fuzzy best-worst method is used to weigh the criteria, and the interval VIKOR technique is applied to evaluate the suppliers in the presence of uncertainty. This study contributes to the sustainable development goals (SDG's) of providing Decent Work and Economic Growth (SDG 8) and Responsible Consumption and Production (SDG 12). The proposed method is then used to evaluate six suppliers in the wire-and-cable industry in Iran. The results obtained from the implementation of the proposed approach and its sensitivity analysis indicate the applicability and efficiency of the proposed approach.
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•Proposed a new framework for sustainable circular supplier selection•Proposed new approach based on the streaming data•Proposed fuzzy best-worst method (BWM) and interval VIKOR method•Validated the framework using case study from cable and wire production company
Despite multiple efficacious therapies in common between psoriasis (PS) and Ulcerative Colitis (UC), mechanisms underlying their common pathophysiology remain largely unclear. Here we sought to ...establish a link by evaluating expression differences and pathway alterations in diseased tissues. We identified two sets of differentially expressed genes (DEGs) between lesional and nonlesional tissues in meta-analyses of data collected from baseline samples in 3 UC and then 3 PS available clinical studies from Pfizer. A shared gene signature was defined by 190 DEGs common to both diseases. Commonly dysregulated pathways identified via enrichment analysis include interferon signaling, partly driven by genes IFI6, CXCL9, CXCL10 and CXCL11, which may attract chemotaxis of Th1 cells to inflammatory sites; IL-23 pathway (IL-23A, CCL20, PI3, CXCL1, LCN2); and Th17 pathway except IL-17A. Elevated expression of costimulatory molecules ICOS and CTLA4 suggests ongoing T-cell activation in both diseases. The clinical value of the shared signature is demonstrated by a gene set improvement score reflecting post-treatment molecular improvement for each disease. This is the first study using transcriptomic meta-analysis to define a tissue gene signature and pathways dysregulated in both PS and UC. These findings suggest immune mechanisms may initiate and sustain inflammation similarly in the two diseases.
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