Develop new strategies to design and operate the multilateration systems, used for air traffic control operations, in a more efficient way. The design strategies are based on the utilization of metaheuristic optimization techniques and they are intended to found the optimal spatial distribution of the system ground stations, taking into account the most relevant system operation parameters. The strategies to operate the systems are based on the development of new positioning methods which allow solving the problems of uncertainty position and poor accuracy that the current systems can present. The new strategies can be applied to design, deploy and operate the multilateration systems for airport surface surveillance as well as takeoff-landing, approach and enroute control. An important advance in the current knowledge of air traffic control is expected from the development of these strategies, because they solve several deficiencies that have been made clear, by the international scientific community, in the last years. / Mantilla Gaviria, IA. (2013). New Strategies to Improve Multilateration Systems in the Air Traffic Control [Tesis doctoral]. Editorial Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/29688

POD (Point of Dispensing)-based emergency response plans involving mass prophylaxis may seem feasible when considering the choice of dispensing points within a region, overall population density, and estimated traffic demands. However, the plan may fail to serve particular vulnerable sub-populations, resulting in access disparities during emergency response. Federal authorities emphasize on the need to identify sub-populations that cannot avail regular services during an emergency due to their special needs to ensure effective response. Vulnerable individuals require the targeted allocation of appropriate resources to serve their special needs. Devising schemes to address the needs of vulnerable sub-populations is essential for the effectiveness of response plans. This research focuses on data-driven computational methods to quantify and address vulnerabilities in response plans that require the allocation of targeted resources. Data-driven methods to identify and quantify vulnerabilities in response plans are developed as part of this research. Addressing vulnerabilities requires the targeted allocation of appropriate resources to PODs. The problem of resource allocation to PODs during public health emergencies is introduced and the variants of the resource allocation problem such as the spatial allocation, spatio-temporal allocation and optimal resource subset variants are formulated. Generating optimal resource allocation and scheduling solutions can be computationally hard problems. The application of metaheuristic techniques to find near-optimal solutions to the resource allocation problem in response plans is investigated. A vulnerability analysis and resource allocation framework that facilitates the demographic analysis of population data in the context of response plans, and the optimal allocation of resources with respect to the analysis are described.