Indigenous rights’ relationship to ecological justice in Amazonia has not been explicitly explored in the literature. As social scientists rarely talk about violence against non-humans, this case study of conservation in Amazonia will explore this new area of concern. Ethical inquiries in conservation also engage with the manifold ways through which human and nonhuman lives are entangled and emplaced within wider ecological relationships, converging in the notion of environmental justice, which often fails to account for overt violence or exploitation of non-humans. Reflecting on this omission, this chapter discusses the applicability of engaged social science and conservation to habitat destruction in Amazonia, and broader contexts involving violence against non-humans. The questions addressed in this chapter are: is the idea of ecological justice sufficiently supported in conservation debate, and more practical Amazonian contexts? Can advocacy of inherent rights be applied to the case of non-humans? Can indigenous communities still be considered 'traditional' considering population growth and increased consumptive practices? Concluding that the existing forms of justice are inadequate in dealing with the massive scale of non-human abuse, this chapter provides directions for conservation that engage with deep ecology and ecological justice in the Amazonian context. doi: 10.1007/978-3-030-29153-2 LinkedIn: https://www.linkedin.com/in/helenkopnina/
MULTIFILE
This study tackles the gate allocation problem (GAP) at the airport terminal, considering the current covid-19 pandemic restrictions. The GAP has been extensively studied by the research community in the last decades, as it represents a critical factor that determines an airport's capacity. Currently, the airport passenger terminal operations have been redesigned to be aligned and respect the covid-19 regulation worldwide. This provides operators with new challenges on how to handle the passengers inside the terminal. The purpose of this study is to come up with an efficient gate allocator that considers potential issues derived by the current pandemic, i.e., avoid overcrowded areas. A sim-opt approach has been developed where an evolutionary algorithm (EA) is used in combination with a dynamic passenger flow simulation model to find a feasible solution. The EA aims to find a (sub)optimal solution for the GAP, while the simulation model evaluates its efficiency and feasibility in a real-life scenario. To evaluate the potential of the Opt-Sim approach, it has been applied to a real airport case study.
