Relief Supply Chain Management Using Internet of Things to Address COVID-19 Outbreak.

Nowadays, due to the COVID-19 outbreak, the most significant factor to be considered all over the world is to manage this pandemic and especially to address positive cases, efficiently and effectively. This can be achieved by simultaneously utilizing the present network with supply chain settings and also the Internet of Things (IoT). This consideration enables the accurate monitoring of suspected cases in real-time to optimize total service time. Hence, this paper firstly designs two sub-models to minimize distance and traffic while minimizing total response time. Our main contribution in this paper is to develop a dynamic scheme using IoT to deal with suspected cases. We also investigate the proposed methodology on a real case problem in Canada. A comprehensive analysis of the proposed methodology behavior has been conducted and the results showed the managerial decision-making process to address COVID-19 patients. The proposed approach establishes efficient strategies to identify suspicious COVID-19 cases and provide them with medical observance in a short time when utilized with IoT. The obtained results of the considered scenarios show 12% up to 15% improvement in the ambulance response time when using IoT.

A novel two-phase robust portfolio selection and optimization approach under uncertainty: A case study of Tehran stock exchange.

Portfolio construction is one of the most critical problems in financial markets. In this paper, a new two-phase robust portfolio selection and optimization approach is proposed to deal with the uncertainty of the data, increasing the robustness of investment process against uncertainty, decreasing computational complexity, and comprehensive assessments of stocks from different financial aspects and criteria are provided. In the first phase of this approach, all candidate stocks' efficiency is measured using a robust data envelopment analysis (RDEA) method. Then in the second phase, by applying robust mean-semi variance-liquidity (RMSVL) and robust mean-absolute deviation-liquidity (RMADL) models, the amount of investment in each qualified stock is determined. Finally, the proposed approach is implemented in a real case study of the Tehran stock exchange (TSE). Additionally, a sensitivity analysis of all robust models of this study is examined. Illustrative results show that the proposed approach is effective for portfolio selection and optimization in the presence of uncertain data.

Assessing the use of Radio Frequency Identification technologies as an alternative for insurance costs in hospitals.

OBJECTIVES: This research assesses the use of Radio Frequency Identification (RFID) technologies as an alternative for insurance costs in hospitals. METHODS: Despite the advantages of RFID, this technology has not been applied in most hospitals due to implementation costs and amortization of RFID. In this paper, we intend to model the total profit of hospitals in three scenarios namely, application of RFID technology in the hospital, without applying RFID technology in the hospital and insuring patients and equipment in the hospital. RESULTS: We analyzed the aforementioned situations over a period of time to find out how they affect the profit of the hospital. Based on this analysis we concluded that if applying RFID technology is costly, it will be feasible for advanced hospitals with more beds. In the scenario of insuring patients and equipment, if insurance organization takes over a small portion of the cost of the mistakes and oversights, insuring patients and equipment will not be feasible for the hospital, and it is better to apply RFID technology Instead. CONCLUSIONS: RFID is among the technologies applied to reduce mistakes of the personnel in hospitals. Moreover, applying this technology has led to a decrease in the number of personnel required in hospitals. This study models total profit of hospitals in three aforementioned scenarios. Based on analyzing these models we conclude that if applying RFID technology is costly, it will be feasible for advanced hospitals with more beds.

Integrating strategic and tactical decisions in livestock supply chain using bi-level programming, case study: Iran poultry supply chain.

Inventory management has frequently been targeted by researchers as one of the most pivotal problems in supply chain management. With the expansion of research studies on inventory management in supply chains, perishable inventory has been introduced and its fundamental differences from non-perishable inventory have been emphasized. This article presents livestock as a type of inventory that has been less studied in the literature. Differences between different inventory types, affect various levels of strategic, tactical and operational decision-making. In most articles, different levels of decision-making are discussed independently and sequentially. In this paper, not only is the livestock inventory introduced, but also a model has been developed to integrate decisions across different levels of decision-making using bi-level programming. Computational results indicate that the proposed bi-level approach is more efficient than the sequential decision-making approach.