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This dissertation by Emil Karlsson explores optimization methods for addressing large-scale avionics scheduling problems. The work is situated within the context of modern aircraft systems where integrated modular avionics architecture plays a pivotal role. The thesis investigates the challenges of ensuring sufficient computing and network resources for tasks in avionic systems, aiming to prevent software failures that could lead to severe consequences. Karlsson's research introduces various methods, including Mixed-Integer Programming (MIP) and Logic-Based Benders Decomposition (LBBD), to develop feasible scheduling solutions. These methods are tested on numerous instances, demonstrating the capability to solve complex scheduling problems efficiently. The intended audience includes researchers and professionals in applied mathematics and avionics engineering.
Avionics. --- Scheduling.
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Scheduling is defined as the process of assigning operations to resources over time to optimize a criterion. Problems with scheduling comprise both a set of resources and a set of a consumers. As such, managing scheduling problems involves managing the use of resources by several consumers. This book presents some new applications and trends related to task and data scheduling. In particular, chapters focus on data science, big data, high-performance computing, and Cloud computing environments. In addition, this book presents novel algorithms and literature reviews that will guide current and new researchers who work with load balancing, scheduling, and allocation problems.
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