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Found 3 papers, 1 papers with code
Towards Multi-Objective High-Dimensional Feature Selection via Evolutionary Multitasking
A task-specific knowledge transfer mechanism is designed to leverage the advantage information of each task, enabling the discovery and effective transmission of high-quality solutions during the search process.
A Survey on Learnable Evolutionary Algorithms for Scalable Multiobjective Optimization
This paper begins with a general taxonomy of scaling-up MOPs and learnable MOEAs, followed by an analysis of the challenges that these MOPs pose to traditional MOEAs.
Benchmark Problems for CEC2021 Competition on Evolutionary Transfer Multiobjectve Optimization
Evolutionary transfer multiobjective optimization (ETMO) has been becoming a hot research topic in the field of evolutionary computation, which is based on the fact that knowledge learning and transfer across the related optimization exercises can improve the efficiency of others.
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