標題: | A robust evolutionary algorithm for global optimization |
作者: | Yang, JM Lin, CJ Kao, CY 生物科技學系 生物資訊及系統生物研究所 Department of Biological Science and Technology Institude of Bioinformatics and Systems Biology |
關鍵字: | evolutionary algorithms;family competition;multiple mutation operators;adaptive rules;global optimization |
公開日期: | 2002 |
摘要: | This paper studies an evolutionary algorithm for global optimization. Based on family competition and adaptive rules, the proposed approach consists of global and local strategies by integrating decreasing-based mutations and self-adaptive mutations. The proposed approach is experimentally analyzed by showing that its components can integrate with one another and possess good local and global properties. Following the description of implementation details, the approach is then applied to several widely used test sets, including problems from international contests on evolutionary optimization. Numerical results indicate that the new approach performs very robustly and is competitive with other well-known evolutionary algorithms. |
URI: | http://hdl.handle.net/11536/29100 http://dx.doi.org/10.1080/03052150214019 |
ISSN: | 0305-215X |
DOI: | 10.1080/03052150214019 |
期刊: | ENGINEERING OPTIMIZATION |
Volume: | 34 |
Issue: | 5 |
起始頁: | 405 |
結束頁: | 425 |
顯示於類別: | 期刊論文 |