Exploring Long-term Memory in Evolutionary Multi-objective Algorithms: A Case Study with NSGA-III

In the field of many-objective optimization, obtaining a dense solution set is a challenging task, mostly due to having hyper-surface nature of Pareto-front; which cannot be covered by commonly utilized population sizes. This is particularly vital in scenarios where innovization and informed decisio...

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Vydáno v:	Conference proceedings - Canadian Conference on Electrical and Computer Engineering s. 864 - 870
Hlavní autoři:	Poor, Masoud Kermani, Rahnamayan, Shahryar, Bidgoli, Azam Asilian, Ebrahimi, Mehran
Médium:	Konferenční příspěvek
Jazyk:	angličtina
Vydáno:	IEEE 06.08.2024
Témata:	Archive Artificial neural networks Benchmark testing Decision making Evolutionary computation IGD Knee points Long-term memory Many-objective optimization NSGA-III Optimization Pareto-front coverage Training
ISSN:	2576-7046
On-line přístup:	Získat plný text
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