计算机应用 ›› 2011, Vol. 31 ›› Issue (09): 2522-2525.DOI: 10.3724/SP.J.1087.2011.02522

• 人工智能 • 上一篇    下一篇

基于二次插值法的社会情感优化算法

武建娜1,2,崔志华1,2,3,刘静1,2   

  1. 1. 太原科技大学 复杂系统与计算智能实验室,太原 030024
    2. 太原科技大学 计算机科学与技术学院,太原 030024
    3. 南京大学 计算机软件新技术国家重点实验室,南京 210093
  • 收稿日期:2011-03-28 修回日期:2011-05-17 发布日期:2011-09-01 出版日期:2011-09-01
  • 通讯作者: 崔志华
  • 作者简介:武建娜(1981-),女,河南新乡人,硕士研究生,主要研究方向:智能计算;
    崔志华(1976-),男,河北唐山人,副教授,博士,CCF会员,主要研究方向:智能计算;
    刘静(1962-),女,山西太原人,副教授,主要研究方向:智能计算。
  • 基金资助:
    教育部科学技术研究重点项目(209021)

Social emotional optimization algorithm based on quadratic interpolation method

WU Jian-na1,2,CUI Zhi-hua1,2,3,LIU Jing1,2   

  1. 1. Complex System and Computational Intelligence Laboratory, Taiyuan University of Science and Technology, Taiyuan Shanxi 030024, China
    2. School of Computer Science and Technology, Taiyuan University of Science and Technology, Taiyuan Shanxi 030024, China
    3. State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing Jiangsu 210093, China
  • Received:2011-03-28 Revised:2011-05-17 Online:2011-09-01 Published:2011-09-01
  • Contact: CUI Zhi-hua

摘要: 社会情感优化算法是一种模拟人类社会行为的新型群智能优化算法,算法中考虑了个体决策能力以及个体的情感对寻优结果的影响,因此算法的多样性比常见的群智能算法改善了很多,但是局部搜索能力还有待提高。二次插值法是一种局部搜索能力较强的搜索方法,把二次插值法引入社会情感优化算法,搜索效果会改善。通过使用测试函数对算法的优化性能进行测试,证明把二次插值法引入社会情感优化算法,可以使得社会情感优化算法的局部搜索能力增强,从而增强了社会情感优化算法的全局搜索能力。

关键词: 社会情感优化算法, 个体决策能力, 个体情感, 二次插值法, 全局搜索能力

Abstract: Social Emotional Optimization Algorithm (SEOA) is a new swarm intelligent population-based optimization algorithm to simulate the human social behaviors. The individual decision-making ability and individual emotion which have impact on optimization results were taken into account, so the diversity of the algorithm has been improved a lot than common swam intelligence algorithms. However, the local search capacity needs to be updated. Quadratic interpolation method is better-behaved in local search. Therefore, the introduction of it into SEOA will improve the search capability. According to the test for the optimization performance by using benchmark functions, it is proved that the local search ability can be improved by introducing quadratic interpolation method into SEOA, thus increasing the global search capability.

Key words: social emotional optimization algorithm, individual decision-making ability, individual emotion, quadratic interpolation method, global search capability

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