A game theory data science-based mechanism for licensed pharmaceutical products concerning their deterioration: a case of a micro, small, and medium enterprise in Iran.

One of the main characteristics of health systems and pharmaceutical supply chains is their significant costs in the public sector, which has forced governments and companies active in this field to find ways to reduce costs. In this paper, the deterioration of imported pharmaceutical items is investigated as one of the challenges of the supply chain of pharmaceutical firms. Specifically, the micro, small medium enterprise (MSME), and a collaborative strategy to reduce its costs is presented. The technical solution of the cooperative strategy is the formation of a partnership alliance between the foreign patent holder of brand drugs and a domestic manufacturer through an exclusive license contract in the local country. This leads to a significant reduction of costs in the distribution network of the pharmaceutical supply chain. On the other hand, supply chain management techniques in the cooperative strategy provide the necessary motivation for its practical implementation by splitting fair profits between producers and other members, namely local government, distributors, and pharmacies. For these purposes, a cooperative game theory-based contract is utilized to set the parameters of the license agreement, and then a profit-sharing mechanism is introduced that splits the benefits of cooperation among the supply chain members based on their afforded costs. The most important contribution of the current research is to propose an integrated framework that combines the logistics network models, valuation methods, and profit split mechanisms that embody more facts from real-world problems than separate models in this regard in previous studies. Moreover, results of the proposed strategy in the supply chain of a drug for thalassemia patients in Iran indicate the effectiveness of the proposed strategy in reducing costs and deterioration. Further, it is shown that the higher the ordering costs of the imported drugs, the lower the market share of the patent holder, and the lower the financing expenses of the cooperative alliance, the more efficient is the proposed strategy.

COVID19 epidemic outbreak: operating rooms scheduling, specialty teams timetabling and emergency patients' assignment using the robust optimization approach.

The health care system is characterized by limited resources, including the physical facilities as well as skilled human resources. Due to the extensive fixed cost of medical facilities and the high specialization required by the medical staff, the problem of resource scarcity in a health care supply chain is much more acute than in other industries. In the pandemic of the Coronavirus, where medical services are the most important services in communities, and protective and preventive guidelines impose new restrictions on the system, the issue of resource allocation will be more complicated and significantly affect the efficiency of health care systems. In this paper, the problem of activating the operating rooms in hospitals, assigning active operating rooms to the COVID-19 and non-COVID-19 patients, assigning specialty teams to the operating rooms and assigning the elective and emergency patients to the specialty teams, and scheduling their operations is studied by considering the new constraints of protective and preventive guidelines of the Coronavirus. To address these issues, a mixed-integer mathematical programming model is proposed. Moreover, to consider the uncertainty in the surgery duration of elective and emergency patients, the stochastic robust optimization approach is utilized. The proposed model is applied for the planning of operating rooms in the cardiovascular department of a hospital in Iran, and the results highlight the role of proper management in supplying sufficient medical resources effectively to respond to patients and scheduled surgical team to overcome the pressure on hospital resources and medical staff results from pandemic conditions.

Sustainability performance evaluation of the E-waste closed-loop supply chain with the SCOR model.

From a sustainability perspective, the performance of a company's supply chain will be satisfactory when it has reached in all aspects a desirable eco-environmentally friendly level. Assessing the sustainability performance in the closed-loop e-waste supply chain becomes vital because its activities are primarily targeted towards sustainability goals related to the process of production, supply, recycling, and disposal of electrical components. This study evaluates the performance of e-waste supply chain sustainability and identifies its performance indicators as a framework for evaluating supply chain performance using the Best-Worst Method (BWM), which is a multi-criteria decision-making (MCDM) approach. For this, the supply chain operations reference (SCOR) model is considered the basic performance evaluation reference. Moreover, through reviewing the literature, the complementary indicators of this model, especially in terms of sustainability, are added to the performance evaluation indices using the Nominal Group Technique (NGT). After specifying and forming a performance evaluation hierarchy, the BWM method is used to determine the criteria score. The results of implementing the framework on some well-known supply chains in New Zealand indicate that the attributes of "Costs," "Quality," and "GreenScor" are crucial for achieving high performance, while in this developed country, there is less concern about social issues.