Graph Learning-based Dynamic Multi-objective Optimization Algorithm

Dynamic Multi-objective Optimization Problems (DMOPs) involve multiple conflicting objective functions that evolve over time. Solving DMOPs requires Dynamic Multiobjective Optimization Algorithms (DMOAs) capable of tracking the dynamic evolution of the Pareto-optimal Front (POF) in real time. In rec...

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Vydané v:	2025 7th International Conference on Data-driven Optimization of Complex Systems (DOCS) s. 283 - 288
Hlavní autori:	Wang, Chi, Song, Wei
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 19.08.2025
Predmet:	Accuracy Benchmark testing Computational modeling Dynamic multi-objective optimization Evolutionary computation Graph Learning Heuristic algorithms Optimization Partitioning algorithms Prediction algorithms Prediction model Predictive models Time series analysis
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