Abstract
Many optimization problems involve multiple objectives, constraints and parameters that change over time. These problems are called dynamic multiobjective optimization problems (DMOPs) and have recently attracted a lot of research. In this chapter, we provide a survey of the state-of-the-art on the field of dynamic multi-objective optimization with regards to the definition and classification of DMOPS, test problems, performance measures and optimization approaches. We provide a comprehensive definition of DMOPs and identify gaps, challenges and future works in dynamic multi-objective optimization. © 2013 Springer-Verlag Berlin Heidelberg.
| Original language | English |
|---|---|
| Title of host publication | Evolutionary Computation for Dynamic Optimization Problems |
| Editors | Shengxiang YANG, Xin YAO |
| Publisher | Springer |
| Chapter | 4 |
| Pages | 85-106 |
| Number of pages | 22 |
| ISBN (Electronic) | 9783642384165 |
| ISBN (Print) | 9783642384158, 9783642448430 |
| DOIs | |
| Publication status | Published - 2013 |
| Externally published | Yes |
Publication series
| Name | Studies in Computational Intelligence |
|---|---|
| Publisher | Springer |
| Volume | 490 |
| ISSN (Print) | 1860-949X |
| ISSN (Electronic) | 1860-9503 |
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Dive into the research topics of 'Dynamic multi-objective optimization: A survey of the state-of-the-art'. Together they form a unique fingerprint.Research output
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Evolutionary Computation for Dynamic Optimization Problems
YANG, S. (Editor) & YAO, X. (Editor), 2013, Heidelberg: Springer. 470 p. (Studies in Computational Intelligence; vol. 490)Research output: Scholarly Books | Reports | Literary Works › Book (Editor) › Research › peer-review
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