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An encyclopedic overview of the Pareto front, the set of Pareto-efficient solutions in multi-objective optimization, commonly used in engineering to evaluate trade-offs.
This paper introduces SCOPE-FL, a hierarchical federated learning framework that uses the Top Trading Cycle algorithm to ensure strategy-proofness and Pareto efficiency in client selection, with reward distribution via Shapley value approximation and blockchain-based execution.