One of the most important issues in disaster response phase is to supply the RELIEF items which is needed by affected areas. The uncertainty of this demand causes many problems. This paper presents a novel robust possibilistic programming model for a routing and scheduling problem in a RELIEF commodities DISTRIBUTION network under demand uncertainty. In RELIEF commodities DISTRIBUTION operations, the possibility of servicing each affected area by multiple vehicles and time window constraint have been considered. The objective of the proposed model is to reduce the total time required by the RELIEF vehicles to reach the affected areas. The fourth region of Tehran city as a case study is provided to illustrate the performance and applicability of the proposed model. Finally, to assess the robustness of the solutions obtained by the novel robust optimization model, they are compared to those generated by the deterministic mixed-integer linear programming model in a number of realizations under different test problems.

Disaster RELIEF logistics is one of the major activities in disaster management. The significance of accounting for uncertainty in such context stimulates an interest to develop appropriate decision making tools to cope with uncertain and imprecise parameters in RELIEF logistics SYSTEM design problems. This paper proposes a multi-objective possibilistic non-linear programming model (MOPNLP) to deal with such issues. Our multi-objective model contains: (i) the minimization of the sum of setup cost, transportation costs and shortage costs of commodity in affected area, (ii) the maximization customer satisfaction. The model includes the imprecise nature of some critical parameters such as demands for various types of RELIEF commodities, cost coefficients and capacity levels. To solve the proposed model, a two-phase interactive fuzzy solution approach is developed. Numerical experiments demonstrate the significance and applicability of the developed possibilistic model as well as the usefulness of the proposed solution approach for actual decision making problem.

Digital soil mapping (DSM) can be defined as a production of spatial soil information. Decision tree (DT) algorithm is one of the most popular machine learning methods which was applied in several recent DSM studies. This study was carried out to evaluate the capability of DT in mapping soils in Miandarband region with area of 50, 000 ha in Kermanshah province. The C5. 0 decision tree algorithm (with and without boosting meta-algorithm) used to establish spatial relationships between known soil taxonomic classes and environmental variables. Using simple SYSTEMatic sampling, 78 pedons were studied and 6 great groups and 14 subgroups of Soil Taxonomy (ST) were identified. Thirty environmental items were derived from a digital elevation model (DEM) file and a landsat-8 OLI/TIRS (July/Tir 1394) image of the area. Predictions made by C5. 0 algorithm showed OA values of 73 percent for great group and subgroup, while comparable values for Kappa Index were 0. 61 and 0. 63, respectively. Combination of boosting meta-algorithm with C5. 0 increased OA values for ST categories 0. 80 and 0. 76 and Kappa Index values to 72 percent and 66 percent. Results showed a considerable capability for DT in recognition of soil pattern over the study area and the topographic variables seems to be most important. Also, analysis of the produced maps, compared with the observed soil pattern during the field survey, revealed a reasonable agreement of decision tree algorithm predictions with reality.

Natural disasters are highly likely to lead to severe problems, including extensive human misery and physical loss or damage. In order to primarily reduce loss of human life, it is vital to respond quickly to natural disasters.One stage of disaster RELIEF operations is in dealing with disaster response, an aspect of which is logistics.Both the DISTRIBUTION of disaster RELIEF to the a effected areas and the evacuation process of injured victims to temporary medical facilities are major activities in disaster RELIEF logistics in the disaster response phase. The predictive analysis of natural disasters and their consequences is challenging because of uncertainties and incomplete data. The significance of accounting for uncertainty in the context of disaster RELIEF logistics stimulates an interest in developing appropriate decision making tools to cope with uncertain and imprecise parameters in RELIEF logistics design.This paper proposes a multi-objective, multi-mode, fuzzy mathematical programming model under the inherent uncertainty of input data in such a problem. The proposed model integrates strategic planning, such as the location of RELIEF DISTRIBUTION centers, with tactical support decisions, i.e., the quantity of flow between facilities to avoid separate decision-making processes between strategic and tactical levels. Furthermore, the model considers the determination of the location of temporary medical facilities after natural disaster occurrences.In our approach, not only demands, but also supplies and the cost of transportation, are considered as the fuzzy parameters. According to recent studies, the performance of RELIEF operations is measured based on total cost and demand satisfaction levels. Therefore, our multi-objective model contains: (i) minimization of the sum of the setup cost, transportation costs, vehicle assignment costs and shortage costs; (ii) maximization of serving injured people. To solve the proposed fuzzy multi-objective optimization model, an interactive fuzzy solution approach, based on the epsilon constraint method, is proposed, because of its capability of measuring and adjusting the satisfaction levels of each objective function explicitly. A case study is used to demonstrate the significance and applicability of the developed fuzzy optimization model, as well as the usefulness of the proposed solution approach.

Throughout history, nature has exposed humans to destructive phenomena such as earthquakes, floods, droughts, tornadoes, volcanic eruptions, and tropical and marine storms. The large scale of damages and casualties caused by natural disasters around the world has led to extensive applied research in the field of preparation and development of a comprehensive SYSTEM for disaster management to minimize the resulting casualties and financial damages. Based on this motivation and challenges to the field, this research designs an integrated RELIEF chain to optimize simultaneously the preparedness and response phases of disaster management. Decisions to improve the supply chain include locating DISTRIBUTION centers of RELIEF supplies; the amount of inventory stored in facilities in pre-disaster phase, locating temporary care centers and transportation points of the injured, how to allocate RELIEF services to the affected areas, and routing of the vehicles used to distribute RELIEF supplies and evacuate the injured. The results show that decreasing the capacity of DISTRIBUTION centers increases the amount of shortage of supplies and increasing the capacity of these centers reduces the amount of shortage of supplies.

One of the obvious reasons for most disorders in network service provisioning is network path congestion. Congestion avoidance in today's networks is too costly and sometimes impossible. With the introduction of SDN, centralizing the equipment's control plane has become possible. This paper presents an enhanced method named ESV-DBRA to avoid congestion in multi-tenant SDN networks. At first, ESV-DBRA monitors the traffic load and delay of all network paths for each tenant individually. Then, by merging the parameters obtained from the monitoring, the Service Level Agreements (SLA), and a novel proposed cost function, it calculates the cost of the network paths per tenant. As a result, traffic for each tenant is routed through the path/paths at the lowest possible cost from the tenant's perspective. Next, the bandwidth quotas will be calculated and assigned to the tenants over their optimal routes. Afterward, whenever congestion is likely to occur in a path, ESV-DBRA automatically changes the route or bandwidth of the tenants' traffic related to this path to avoid congestion. Related algorithms are also proposed.Eventually, simulations show that the proposed method effectively increases bandwidth utilization by 10.76%.

INTRODUCTION: The frequency of natural disasters is high in Iran due to its special climatic and geophysical conditions. However, the provision of better services to trauma victims requires further research. Decisions on emergency accommodation and meeting the needs of the victims are often made in conditions of uncertainty, and the lack of appropriate studies leads to the provision of low-quality and intermittent services. METHODS: This applied and descriptive-analytical study was conducted to determine the advantages and disadvantages of RELIEF tents using documentary and library resources, observation, and interviews with officials and experts, and the effective standards for the construction SYSTEM of emergency accommodation. The thermal comfort of the victims was then investigated using the guidelines of the American Society of Heating, Refrigerating, and Air-Conditioning Engineers (ASHRAE), interviews with the victims, and field tests. Moreover, solutions are introduced for the improvement and optimization of RELIEF tents, and a new building SYSTEM is introduced for the emergency accommodation of victims in incidents by removing the disadvantages of the SYSTEMs previously used in emergency accommodation. FINDINGS: According to the observations and investigations, the previously used emergency shelters do not meet the needs of the accident survivors properly and their design does not correspond to the users’,culture and needs. The problems with the current accommodating methods include lack of privacy, lack of protection against disturbing cold and heat, and inappropriate and non-standard dimensions of the existing tents. Solutions have been presented to solve the existing problems and a new SYSTEM for emergency accommodation has been introduced based on field observations and interviews with experts. CONCLUSION: It is noteworthy that the votes of 22 percent of people are in the range of slightly warm to slightly cold,which shows that these people are satisfied with their accommodation regarding thermal comfort. 78 percent of the people's votes were outside the satisfaction range. Due to the chambered structure of the tent, direct sunlight in the summer, the lack of proper air exchange, the weakness of the structural components of the tent and the lack of heat retention in the winter, proper mechanical SYSTEMs should be used to provide thermal comfort, which is not feasible in practice due to the extent of the incidents and large amounts of equipment and resources needed which bolds the importance of the proposed construction SYSTEM.