Dynamic Multiobjective Optimization with Multiple Response Strategies Based on Linear Environment Detection
Dynamic multiobjective optimization problems (DMOPs) bring more challenges for multiobjective evolutionary algorithm (MOEA) due to its time-varying characteristic. To handle this kind of DMOPs, this paper presents a dynamic MOEA with multiple response strategies based on linear environment detection...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2020/9053809 |
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| _version_ | 1832566050556739584 |
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| author | Qiyuan Yu Shen Zhong Zun Liu Qiuzhen Lin Peizhi Huang |
| author_facet | Qiyuan Yu Shen Zhong Zun Liu Qiuzhen Lin Peizhi Huang |
| author_sort | Qiyuan Yu |
| collection | DOAJ |
| description | Dynamic multiobjective optimization problems (DMOPs) bring more challenges for multiobjective evolutionary algorithm (MOEA) due to its time-varying characteristic. To handle this kind of DMOPs, this paper presents a dynamic MOEA with multiple response strategies based on linear environment detection, called DMOEA-LEM. In this approach, different types of environmental changes are estimated and then the corresponding response strategies are activated to generate an efficient initial population for the new environment. DMOEA-LEM not only detects whether the environmental changes but also estimates the types of linear changes so that different prediction models can be selected to initialize the population when the environmental changes. To study the performance of DMOEA-LEM, a large number of test DMOPs are adopted and the experiments validate the advantages of our algorithm when compared to three state-of-the-art dynamic MOEAs. |
| format | Article |
| id | doaj-art-2350e845b7eb4a9c879586497dac8978 |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-2350e845b7eb4a9c879586497dac89782025-02-03T01:05:10ZengWileyComplexity1076-27871099-05262020-01-01202010.1155/2020/90538099053809Dynamic Multiobjective Optimization with Multiple Response Strategies Based on Linear Environment DetectionQiyuan Yu0Shen Zhong1Zun Liu2Qiuzhen Lin3Peizhi Huang4College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, ChinaCollege of Computer Science and Software Engineering, Shenzhen University, Shenzhen, ChinaCollege of Computer Science and Software Engineering, Shenzhen University, Shenzhen, ChinaCollege of Computer Science and Software Engineering, Shenzhen University, Shenzhen, ChinaCollege of Computer Science and Software Engineering, Shenzhen University, Shenzhen, ChinaDynamic multiobjective optimization problems (DMOPs) bring more challenges for multiobjective evolutionary algorithm (MOEA) due to its time-varying characteristic. To handle this kind of DMOPs, this paper presents a dynamic MOEA with multiple response strategies based on linear environment detection, called DMOEA-LEM. In this approach, different types of environmental changes are estimated and then the corresponding response strategies are activated to generate an efficient initial population for the new environment. DMOEA-LEM not only detects whether the environmental changes but also estimates the types of linear changes so that different prediction models can be selected to initialize the population when the environmental changes. To study the performance of DMOEA-LEM, a large number of test DMOPs are adopted and the experiments validate the advantages of our algorithm when compared to three state-of-the-art dynamic MOEAs.http://dx.doi.org/10.1155/2020/9053809 |
| spellingShingle | Qiyuan Yu Shen Zhong Zun Liu Qiuzhen Lin Peizhi Huang Dynamic Multiobjective Optimization with Multiple Response Strategies Based on Linear Environment Detection Complexity |
| title | Dynamic Multiobjective Optimization with Multiple Response Strategies Based on Linear Environment Detection |
| title_full | Dynamic Multiobjective Optimization with Multiple Response Strategies Based on Linear Environment Detection |
| title_fullStr | Dynamic Multiobjective Optimization with Multiple Response Strategies Based on Linear Environment Detection |
| title_full_unstemmed | Dynamic Multiobjective Optimization with Multiple Response Strategies Based on Linear Environment Detection |
| title_short | Dynamic Multiobjective Optimization with Multiple Response Strategies Based on Linear Environment Detection |
| title_sort | dynamic multiobjective optimization with multiple response strategies based on linear environment detection |
| url | http://dx.doi.org/10.1155/2020/9053809 |
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