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Abstract
In multi-objective optimization problem (MOP), keeping solution diversity is key case for solution quality. To improve the MOP quality, the diversity maintenance threshold value (λα) is proposed to keep solutions diversity based on adaptive grid strategy. These strategies can adaptive maintain the non-inferior diversity to improve swarm individual fly to the global optimal. Four test problems are selected to test the proposed strategy compared with other classical methods, and three performance metrics are chosen to explore the algorithm effectiveness.
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Acknowledgments
This work is supported by the National Natural Science Foundation of China (Grants nos. 71461027, 71001072, 71271140, 71471158). Guizhou province science and technology fund (Qian Ke He J [2012] 2340 and [2012]2342, LKZS [2012]10 and [2012]22); Guizhou province natural science foundation in China (Qian Jiao He KY [2014]295); The educational reform project in guizhou province department of education (Qian jiao gao fa[2013]446); Guizhou province college students’ innovative entrepreneurial training plan(201410664004); 2013 and 2014 Zunyi 15851 talents elite project funding.
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Authors and Affiliations
School of Mathematics and Computer Science, Zunyi Normal College, Zunyi, 563002, China
Yanmin Liu & Rui Liu
College of Management, Shenzhen University, Shenzhen, 518060, China
Ben Niu
Department of Industrial and System Engineering, Hong Kong Polytechnic University, Kowloon, Hong Kong
Felix T. S. Chan
College of Life Science, Zunyi Normal College, Zunyi, 563002, China
Changling Sui
- Yanmin Liu
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- Rui Liu
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- Changling Sui
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Correspondence toYanmin Liu.
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Tongji University, Shanghai, China
De-Shuang Huang
University of Ulsan, Ulsan, Korea (Republic of)
Kang-Hyun Jo
Liverpool John Moores University, Liverpool, United Kingdom
Abir Hussain
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Liu, Y., Niu, B., Chan, F.T.S., Liu, R., Sui, C. (2015). Multi-objective PSO Based on Grid Strategy. In: Huang, DS., Jo, KH., Hussain, A. (eds) Intelligent Computing Theories and Methodologies. ICIC 2015. Lecture Notes in Computer Science(), vol 9226. Springer, Cham. https://doi.org/10.1007/978-3-319-22186-1_71
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