Nov 16, 2022 · A knowledge guided transfer strategy (KTS)-based DMOEA is proposed in this article. First, knowledge described as a two-tuple is extracted under each ...
Experiments on 20 benchmark problems demonstrate that the knowledge guided transfer strategy outperforms five state-of-the-art algorithms, achieving good.
The key task in dynamic multiobjective optimization problems (DMOPs) is to find Pareto-optima closer to the true one as soon as possible once a new ...
Apr 18, 2024 · A Knowledge Guided Transfer Strategy for Evolutionary Dynamic Multiobjective Optimization. Article. Jan 2022; IEEE T EVOLUT COMPUT.
This paper proposes a novel knowledge transfer method for the dynamic multi-objective evolutionary algorithm (T-DMOEA) to solve DMOPs.
... Liang, J.: A knowledge guided transfer strategy for evolutionary dynamic multiobjective optimization. IEEE Trans. Evol. Comput. 27(6), 1750–1764 (2023)
Jul 12, 2024 · This study categorizes and evaluates evolutionary many-task algorithms, differentiating them based on their approaches to knowledge transfer: ...
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Dynamic multiobjective optimization poses great challenges to evolutionary algorithms due to the change of optimal solutions or Pareto front with time. Learning ...
This work proposes a general MTO framework named individually guided multi-task optimization (IMTO). It divides evolutions into vertical and horizontal ones.
Mar 11, 2024 · This algorithm leverages reported knowledge and information from the population in dynamic environments to guide the evolution of diverse ...