Evolutionary large-scale multi-objective optimization and applications integrating evolutionary computation, machine learning, and data science / Xingyi Zhang, Ran Cheng, Ye Tian, Yaochu Jin.
| Author/creator | Zhang, Xingyi |
| Other author | Cheng, Ran (Computer scientist) |
| Other author | Tian, Ye (Associate professor) |
| Other author | Jin, Yaochu, 1966- |
| Format | Electronic |
| Publication Info | Hoboken, New Jersey : Wiley, [2024] |
| Description | pages cm |
| Supplemental Content | Full text available from eBooks on EBSCOhost |
| Subjects |
| Abstract | "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."-- Provided by publisher. |
| Bibliography note | Includes bibliographical references and index. |
| Access restriction | Available only to authorized users. |
| Technical details | Mode of access: World Wide Web |
| Genre/form | Electronic books. |
| LCCN | 2024018004 |
| ISBN | 9781394178414 (hardback) |
| ISBN | (adobe pdf) |
| ISBN | (epub) |
Availability
| Library | Location | Call Number | Status | Item Actions |
|---|---|---|---|---|
| Electronic Resources | Access Content Online | ✔ Available |