Dec 27, 2019 · Multiobjective multitasking optimization (MTO) is an emerging research topic in the field of evolutionary computation.
In contrast to multiobjective optimization, MTO solves multiple optimization tasks simultaneously. MTO aims to improve the overall performance of multiple tasks ...
An MTO algorithm based on incremental learning (EMTIL) is proposed, which demonstrates that EMTIL works more effectively for MTO compared to the existing ...
Oct 22, 2024 · Multi-objective multi-tasking optimization (MTO) is an emerging research topic in the field of evolutionary computation.
We propose an algorithm for incremental-learning model-based multiobjective estimation of distributions. A learning mechanism based on an incremental Gaussian ...
Multitask optimization uses the knowledge transfer between tasks to deal with multiple related tasks simultaneously, which obtains better optimization ...
2. Evolutionary Multitasking via Explicit autoencoding, TCYB, 2018 ; 3. Multiobjective Multitasking OptimizationBased on Incremental Learning, TEVC, 2020 ; 4. An ...
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Multiobjective Multitasking Optimization Based on Incremental Learning. 824 ... A Holistic Study on Preference-Based Evolutionary Multiobjective Optimization ...
Multi-objective multitasking optimization (MTO) is an emerging research topic in the field of evolutionary computation, which can solve multiple ...
Jan 4, 2022 · This paper is the first attempt to design an efficient transfer strategy based on multidirectional prediction method.