Generative Robust Optimisation defines uncertainty sets via neural network decoders over latent spaces and evaluates them with a five-point framework, validated on planning problems using Wasserstein autoencoders.
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Robust optimization framework for green ammonia that ensures feasible capacity plans under renewable uncertainty where constraint aggregation fails, using scenario reduction and adaptive policies.
Introduces the Feasible Sovereign Operating Region (FSOR) as a construct for workloads sustainable under physical and regulatory limits, along with a joint compute-network optimization framework that enforces sustainability as hard constraints.
citing papers explorer
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Generative Robust Optimisation
Generative Robust Optimisation defines uncertainty sets via neural network decoders over latent spaces and evaluates them with a five-point framework, validated on planning problems using Wasserstein autoencoders.
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Robust Optimization for Green Ammonia Production
Robust optimization framework for green ammonia that ensures feasible capacity plans under renewable uncertainty where constraint aggregation fails, using scenario reduction and adaptive policies.
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Sustainability-Constrained Workload Orchestration for Sovereign AI Infrastructure: A Joint Compute-Network Optimization Framework
Introduces the Feasible Sovereign Operating Region (FSOR) as a construct for workloads sustainable under physical and regulatory limits, along with a joint compute-network optimization framework that enforces sustainability as hard constraints.