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A gene expression programming algorithm for multiobjective site-search problem

  • Mengwei Liu*
  • , Xia Li
  • , Tao Liu
  • , Dan Li
  • , Lin Zheng
  • *此作品的通讯作者

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Multiobjective site selection is a class complicated spatial analysis problem which can hardly be solved with traditional methods of Geographical Information System (GIS). In this paper we described an approach based on the gene expression programming (GEP) algorithm, with which the multiobjective site-search problems can be resolved. The validity of this method is verified by using MOP2 function, Bohachevsky function and Shubert function. By the comparison with genetic algorithms, it is concluded that the proposed GEP method using the expression trees/simple strings coding strategy can generate more approximate Pareto-front than the GAs using the linear coding method. This proposed model is finally applied to facilities optimal location search in Guangzhou.

源语言英语
主期刊名Proceedings - 2010 6th International Conference on Natural Computation, ICNC 2010
14-18
页数5
DOI
出版状态已出版 - 2010
已对外发布
活动2010 6th International Conference on Natural Computation, ICNC'10 - Yantai, Shandong, 中国
期限: 10 8月 201012 8月 2010

出版系列

姓名Proceedings - 2010 6th International Conference on Natural Computation, ICNC 2010
1

会议

会议2010 6th International Conference on Natural Computation, ICNC'10
国家/地区中国
Yantai, Shandong
时期10/08/1012/08/10

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