Multi-parent Crossover Based Genetic Algorithm for Bi-Objective Unconstrained Binary Quadratic Programming Problem
文献类型：会议论文
| 作者 | Huo, Chao1; Zeng, Rongqiang1,2; Wang, Yang3; Shang, Mingsheng4
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| 出版日期 | 2016 |
| 会议日期 | October 28, 2016 - October 30, 2016 |
| 会议地点 | Xian, China |
| DOI | 10.1007/978-981-10-3614-9_2 |
| 页码 | 10-19 |
| 通讯作者 | Zeng, Rongqiang (zrq@home.swjtu.edu.cn) |
| 英文摘要 | In this paper, we present a multi-parent crossover based genetic algorithm for the bi-objective unconstrained binary quadratic programming problem, by integrating the multi-parent crossover within the framework of hypervolume-based multi-objective optimization algorithm. The proposed algorithm employs a multi-parent crossover operator to generate the offspring solutions, which are used to further improve the quality of Pareto approximation set. Experimental results on 10 benchmark instances demonstrate the efficacy of our proposed algorithm compared with the original multi-objective optimization algorithms. © Springer Nature Singapore Pte Ltd. 2016. |
| 会议录 | 11th International Conference on Bio-inspired Computing – Theories and Applications, BIC-TA 2016
 |
| 语种 | 英语 |
| ISSN号 | 18650929 |
| 源URL | [http://119.78.100.138/handle/2HOD01W0/4671]  |
| 专题 | 大数据挖掘及应用中心 |
| 作者单位 | 1.School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu; Sichuan; 610054, China; 2.School of Mathematics, Southwest Jiaotong University, Chengdu; Sichuan; 610031, China; 3.School of Management, Northwestern Polytechnical University, Xi’an; Shanxi; 710072, China; 4.Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing; 400714, China |
| 推荐引用方式 GB/T 7714 | Huo, Chao,Zeng, Rongqiang,Wang, Yang,et al. Multi-parent Crossover Based Genetic Algorithm for Bi-Objective Unconstrained Binary Quadratic Programming Problem[C]. 见:. Xian, China. October 28, 2016 - October 30, 2016. |
入库方式： OAI收割
来源：重庆绿色智能技术研究院
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