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Found 6 papers, 2 papers with code
Stitching for Neuroevolution: Recombining Deep Neural Networks without Breaking Them
To correct for differing feature representations between these layers we employ stitching, which merges the networks by introducing new layers at crossover points.
The Impact of Asynchrony on Parallel Model-Based EAs
Thus, if an asynchronous parallel MBEA is also affected by an evaluation time bias, this could result in learned models to be less suited to solving the problem, reducing performance.
Solving Multi-Structured Problems by Introducing Linkage Kernels into GOMEA
This cannot be modelled sufficiently well when using linkage models that aim at capturing a single type of linkage structure, deteriorating the advantages brought by MBEAs.
EXPObench: Benchmarking Surrogate-based Optimisation Algorithms on Expensive Black-box Functions
Surrogate algorithms such as Bayesian optimisation are especially designed for black-box optimisation problems with expensive objectives, such as hyperparameter tuning or simulation-based optimisation.
Black-box Mixed-Variable Optimisation using a Surrogate Model that Satisfies Integer Constraints
A challenging problem in both engineering and computer science is that of minimising a function for which we have no mathematical formulation available, that is expensive to evaluate, and that contains continuous and integer variables, for example in automatic algorithm configuration.
Order Acceptance and Scheduling with Sequence-dependent Setup Times: a New Memetic Algorithm and Benchmark of the State of the Art
Sparrow integrates the exploration ability of BRKGA and the exploitation ability of ALNS.
