Data-Driven Evolutionary Algorithm Based on Inductive Graph Neural Networks for Multimodal Multi-Objective Optimization

In multimodal multi-objective optimization problems (MMOPs), multiple solutions on different Pareto optimal solution sets (PSs) are mapped to the same point on the Pareto front. Considering these different solutions can provide users with richer decisions, the search of multiple PSs is crucial when...

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Vydané v:	IEEE transactions on evolutionary computation s. 1
Hlavní autori:	Dang, Qianlong, Liu, Qiqi, Yang, Shuai, He, Xiaoyu
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	IEEE 2025
Predmet:	Adaptation models Data models data-driven evolutionary algorithm Euclidean distance Evolutionary computation Graph neural networks inductive graph neural networks Multimodal multi-objective optimization Network topology Optimization Pareto optimization PSs topology Topology Training
ISSN:	1089-778X, 1941-0026
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