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Found 3 papers, 2 papers with code
Distributed Evolution Strategies with Multi-Level Learning for Large-Scale Black-Box Optimization
In the post-Moore era, main performance gains of black-box optimizers are increasingly depending on parallelism, especially for large-scale optimization (LSO).
Cooperative Coevolution for Non-Separable Large-Scale Black-Box Optimization: Convergence Analyses and Distributed Accelerations
Given the ubiquity of non-separable optimization problems in real worlds, in this paper we analyze and extend the large-scale version of the well-known cooperative coevolution (CC), a divide-and-conquer black-box optimization framework, on non-separable functions.
PyPop7: A Pure-Python Library for Population-Based Black-Box Optimization
In this paper, we present a pure-Python library called PyPop7 for black-box optimization (BBO).
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