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Vector Autoregressive Evolution for Dynamic Multi-Objective Optimisation
Dynamic multi-objective optimisation (DMO) handles optimisation problems with multiple (often conflicting) objectives in varying environments.
An autoencoder wavelet based deep neural network with attention mechanism for multistep prediction of plant growth
Finally, a recurrent neural network including LSTM and an attention mechanism is proposed for modelling long-term dependencies in the time series data.
AREA: Adaptive Reference-set Based Evolutionary Algorithm for Multiobjective Optimisation
The proposed framework is combined with new strategies, such as reference adaptation and adaptive local mating, to solve different types of problems.
A Scalable Test Suite for Continuous Dynamic Multiobjective Optimisation
It is demonstrated with empirical studies that the proposed test suite is more challenging to the dynamic multiobjective optimisation algorithms found in the literature.
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