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Nowadays, logistics is one of the most important tools in disaster relief operations. The logistic planning is essential and a key component in covering the initial needs in the immediate aftermath of any disaster. Planning is both necessary and practical, as it is generally possible to predict the types of disasters that should affect a given location and the needs that such disasters will be likely to cause. Transport planning, reception and distribution of emergency supplies, type and quantity of the resources, the way of procurement and storage of the supplies, the tools of the tracking and means transportation to the stricken area, the specialization of teams participating in the operation and plan of cooperation between these teams, are some vital life-saving coordination roles after natural disasters are connected directly to logistic planning. Turkey is located in one of the most active earthquake and volcanic regions which causes to many major earthquake-prone, in the world with a majority of the population living in these earthquake-prone areas. Earthquakes are one of the major disasters that require emergency logistic planning strategies due to their devastating effects, the large-scale natural disasters could cause major problem on commodities such as food, medicine etc. In this paper, a game theoretical model for emergency logistic planning is developed. To do this a cooperative game model is constructed from a flow problem which occurred after an earthquake in Istanbul. Several solution concepts for maximizing the transferred commodity are given. The paper ends with a conclusion and outlook to future studies. [ABSTRACT FROM AUTHOR]

Due to the high necessity of medical face masks and face shields during the COVID-19 pandemic, healthcare centers dealing with infected patients have faced serious challenges due to the high consumption rate face masks and face shields. In this regard, the supply chain of healthcare centers should put all of their efforts into avoiding any shortages of masks and shields as these products are considered as primary ways to prevent the spread of the virus. Since, any shortages in these products would lead to irrecoverable and costly consequences in terms of the mortality rate of patients and medical staff. Therefore, healthcare centers should decide on best supplier to supply required products, considering technical, and sustainability measures. Dynamicity and uncertainty of the pandemic are other factors that add up to the complexity of the supplier selection problem. Therefore, this paper develops a novel decision-making approach using Measuring attractiveness through a categorical-based evaluation technique (MACBETH) and a new combinative distance-based assessment method to address the supplier selection problem during the COVID-19 pandemic. Due to high uncertainty, vague and incomplete information for decision-making problems during the COVID-19 pandemic, the developed decision-making approach is implemented under fuzzy rough numbers as a superior uncertainty set of the traditional fuzzy set and rough numbers. Extensive sensitivity analysis tests are performed based on parameters of the decision-making approach, impacts of weight coefficients, and consistency of results in comparison to other MCDM methods. A real-life case study is investigated for a hospital in Istanbul, Turkey to show the applicability of the developed approach. Based on the results of MACBETH method, job creation and occupational health and safety systems are two top criteria. Results of the case study for five suppliers indicate that supplier (A1) is the best supplier with a distance score of 3.308. [ABSTRACT FROM AUTHOR]

In natural disasters, having a capable network of collecting and distributing crucial items such as blood is one of the major concerns. However, due to damage to the infrastructure after disasters, mobile blood collecting facilities (blood mobiles) are usually required. This paper aims to decide the locations of mobile facilities in each period for collecting donated blood, plan the blood distribution from the fixed and mobile facilities to the main blood centers, as well as from blood centers to the hospitals and field-hospitals, under uncertain conditions. To do so, a multi-period, bi-objective mixed-integer mathematical model is developed under a multiple-scenario, aiming to minimize the unsatisfied blood demand as well as the total cost of the network. In the proposed model, the blood group compatibility matrix, failure rate of the facilities, and patients' urgency levels are considered. An augmented ε-constraint method is applied to solve this bi-objective model. Due to the complex nature of the proposed blood supply chain model, the Lagrangian relaxation approach is used to solve the proposed model. An expected Istanbul earthquake is considered, and the blood supply planning through the Red Crescent's European branch is performed utilizing the proposed model to examine its validity. According to the numerical results, the mobile facilities' locations in each period under each scenario are determined, the unsatisfied demand in each hospital and field-hospital for each blood type are reported, and the tradeoff between the supply chain costs and unsatisfied demand are discussed in detail. Finally, to illustrate the robustness of the proposed model, a detailed sensitivity analysis is performed. According to the study results, opening new blood centers near the high-demand sub-districts for faster testing and supply, increasing the hospitals' capacities, and usage of drones and helicopters for blood distribution are suggested can be considered as managerial insights. [ABSTRACT FROM AUTHOR]