Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 5 of 5 for “"Embedded Optimization"”.
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Intelligent Digital Twin for Optimizing Warehouse Operations: Embedded Optimization Components for Enhanced Order-Picking Efficiency
… and optimize complex problems. By incorporating optimization and AI-based techniques, DTs facilitate data analysis and accurate simulations, enabling more efficient decision-making. An intelligent warehouse digital twin can simulate the order-picking process, generate improvement scenarios, and …
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Uncertainty, complication and optimal model construction
… described by complicated models with associated embedded optimization requirements. The particular models studied are linear control models in which the embedded optimization is that of observer/ controller design. The existence of an optimal knowledge partition rests on the tradeoff between the …
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Computational analysis of real-time convex optimization for control systems
… software. Nevertheless, analysis of on-line optimization for control has received little attention to date. On-line software must pass rigorous standards in reliability, requiring that any embedded optimization algorithm possess predictable behavior and bounded run-time guarantees. This …
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Hybrid System Identification of Manual Tracking Submovements in Parkinson's Disease
… the dynamics of submovements, then apply hybrid optimization techniques based on embedding to solve a constrained nonlinear program. We also use the existing geometric approach for hybrid system identification to analyze our model and explain the deficits and advantages of each. These methods are …
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Multiagent planning and learning using random decompositions and adaptive representations
… algorithms for heterogeneous teams by using embedded optimization processes to automate the search for decouplings among agents, thus decreasing the dependency on the domain knowledge. Motivated by the low computational complexity and theoretical guarantees of the Bayesian Optimization …