Approximating Pareto Frontiers in Stochastic Multi-Objective Optimization via Hashing and Randomization
Approximating Pareto Frontiers in Stochastic Multi-Objective Optimization via Hashing and Randomization explores XOR-SMOO is a novel algorithm that approximates Pareto frontiers in stochastic multi-objective optimization by querying SAT oracles, outperforming baselines on real-world problems.. Commercial viability score: 7/10 in Optimization Algorithms.
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