UID:
almafu_9961638228202883
Format:
1 online resource (xxiv, 328 pages) :
,
illustrations (some color)
ISBN:
9781394178445
,
1394178441
,
9781394178438
,
1394178433
,
1394178425
,
9781394178421
Content:
"Multi-objective optimization problems (MOPs) widely exist in scientific research and engineering designs. Evolutionary algorithms (EAs) have shown promising potential in solving various MOPs. However, their performance may deteriorate drastically when tackling problems involving a large number of decision variables, i.e., the large-scale multi-objective optimization problems (LSMOPs). In recent years, increasing efforts have been devoted to addressing the challenges brought by such LSMOPs."--
Additional Edition:
Print version: Zhang, Xingyi Evolutionary large-scale multi-objective optimization and applications Hoboken, New Jersey : Wiley, [2024] ISBN 9781394178414
Language:
English
DOI:
10.1002/9781394178445
URL:
https://onlinelibrary.wiley.com/doi/book/10.1002/9781394178445
URL:
https://onlinelibrary.wiley.com/doi/book/10.1002/9781394178445
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