東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Evolutionary large-scale multi-objec...

Zhang, Xingyi.

FindBook

Google Book

Amazon

博客來

Evolutionary large-scale multi-objective optimization and applications = integrating evolutionary computation, machine learning, and data science /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Evolutionary large-scale multi-objective optimization and applications/ Xingyi Zhang ... [et al.]
其他題名:	integrating evolutionary computation, machine learning, and data science /
其他作者:	Zhang, Xingyi.
出版者:	Piscataway, NJ :IEEE ; : c2024.,
面頁冊數:	1 online resource (xxiv, 328 p.) :ill. (some col.)
內容註:	Multi-objective evolutionary algorithms and evolutionary large-scale optimization -- Evolutionary large-scale multi-objective optimization -- Evolutionary algorithms for large-scale multi-objective optimization -- Evolutionary algorithms for sparse large-scale multi-objective optimization -- Evolutionary large-scale multi-objective optimization for community detection in complex networks -- Evolutionary large-scale multi-objective optimization in logistics scheduling -- Evolutionary large-scale multi-objective optimization in power systems -- Evolutionary large-scale multi-objective optimization in radiotherapy planning -- Evolutionary large-scale multi-objective optimization in deep learning.
標題:	Mathematical optimization. -
電子資源:	https://onlinelibrary.wiley.com/doi/book/10.1002/9781394178445
ISBN:	9781394178445

Evolutionary large-scale multi-objective optimization and applications = integrating evolutionary computation, machine learning, and data science /
Evolutionary large-scale multi-objective optimization and applicationsintegrating evolutionary computation, machine learning, and data science /[electronic resource] :Xingyi Zhang ... [et al.] - 1st ed. - Piscataway, NJ :IEEE ;c2024. - 1 online resource (xxiv, 328 p.) :ill. (some col.)

Includes bibliographical references and index.

Multi-objective evolutionary algorithms and evolutionary large-scale optimization -- Evolutionary large-scale multi-objective optimization -- Evolutionary algorithms for large-scale multi-objective optimization -- Evolutionary algorithms for sparse large-scale multi-objective optimization -- Evolutionary large-scale multi-objective optimization for community detection in complex networks -- Evolutionary large-scale multi-objective optimization in logistics scheduling -- Evolutionary large-scale multi-objective optimization in power systems -- Evolutionary large-scale multi-objective optimization in radiotherapy planning -- Evolutionary large-scale multi-objective optimization in deep learning.

"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."--

ISBN: 9781394178445Subjects--Topical Terms:

517763
Mathematical optimization.

LC Class. No.: QA402.5

Dewey Class. No.: 519.6

Evolutionary large-scale multi-objective optimization and applications = integrating evolutionary computation, machine learning, and data science /
LDR:02545cmm a2200325 a 4500 001 2416684
005 20251017072503.0
006 m o d
007 cr cnu---unuuu
008 260303s2024 njua ob 001 0 eng d
020 $a 9781394178445 $q (electronic bk.)
020 $a 1394178441 $q (electronic bk.)
020 $a 9781394178438 $q (electronic bk. ； $q epub)
020 $a 1394178433 $q (electronic bk. ； $q epub)
020 $a 9781394178421 $q (electronic bk. ; $q adobe pdf)
020 $a 1394178425 $q (electronic bk. ; $q adobe pdf)
020 $z 9781394178414 $q (hardback)
035 $a 9781394178445
040 $a NhCcYBP $b eng $c NhCcYBP
041 0 $a eng
050 0 0 $a QA402.5
082 0 0 $a 519.6 $2 23
245 0 0 $a Evolutionary large-scale multi-objective optimization and applications $h [electronic resource] : $b integrating evolutionary computation, machine learning, and data science / $c Xingyi Zhang ... [et al.]
250 $a 1st ed.
260 $a Piscataway, NJ : $b IEEE ; $a Hoboken, NJ : $b John Wiley & Sons, $c c2024.
300 $a 1 online resource (xxiv, 328 p.) : $b ill. (some col.)
504 $a Includes bibliographical references and index.
505 0 $a Multi-objective evolutionary algorithms and evolutionary large-scale optimization -- Evolutionary large-scale multi-objective optimization -- Evolutionary algorithms for large-scale multi-objective optimization -- Evolutionary algorithms for sparse large-scale multi-objective optimization -- Evolutionary large-scale multi-objective optimization for community detection in complex networks -- Evolutionary large-scale multi-objective optimization in logistics scheduling -- Evolutionary large-scale multi-objective optimization in power systems -- Evolutionary large-scale multi-objective optimization in radiotherapy planning -- Evolutionary large-scale multi-objective optimization in deep learning.
520 $a "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."-- $c Provided by publisher.
588 $a Description based on online resource; title from digital title page (viewed on July 24, 2024)
650 0 $a Mathematical optimization. $3 517763
650 0 $a Evolutionary computation. $3 582189
650 0 $a Machine learning. $3 533906
700 1 $a Zhang, Xingyi. $3 3795564
856 4 0 $u https://onlinelibrary.wiley.com/doi/book/10.1002/9781394178445