期刊文献+

群体启发进化规划

Population Heuristic Evolutionary Programming
下载PDF
导出
摘要 本文提出了一种群体启发进化规划(Population Heuristic Evolutionary Programming,PHEP)方法,在进化过程中,通过群体的四个参数,把握群体中个体的分布情况,并通过这些信息有效地调整个体的变异步长,使用标准测试问题对PHEP方法进行了测试和比较,试验数据表明:PHEP方法能够较好地平衡群体压力和选择压力,搜索到的结果要明显优于先前的一些方法。 This paper presents a new method for optimization problem which named population heuristic evolutionary programming (PHEP), it can grasp the information of distribution-status of population by control four parameters of population in the evolution process. PHEP adjusts the mutation size of individual according to such information. Ex- periments for benchmark problem imply that the PHEP can keep the balance of the population press and the selection press very well, the results are great better than other version EP methods.
出处 《计算机科学》 CSCD 北大核心 2005年第7期145-147,167,共4页 Computer Science
基金 国家自然科学基金(批准号:60175024) 教育部"符号计算与知识工程"重点实验室资助
  • 相关文献

参考文献11

  • 1Fogel L J, Owens A J, Walsh M J. Artificial Intelligence Through Simulate Evolution. John Wiley, Chichester, UK,1996
  • 2Yao X,Liu Y, Lin G. Evolutionary Programming Made Faster.IEEE Transactions on Evolutionary Computation, 1999,3 (2): 82~102
  • 3Yao X, Liu Y. Scaling up Evolutionary Programming Algorithms.In:Proc. of the 7th Annual Conf. on Evolutionary Programming,1998. 103~112
  • 4Yao X, Lin G, Liu Y. An Analysis of Evolutionary Algorithms Based on Neighborhood and Step Size. In: Proc. of the 6th Annual Conf. on Evolutionary Programming, Lecture Notes in Computer Science Vol. 1213, Springer-Verlag,1997. 297~307
  • 5Matsumura Y, Ohkura K, Ueda K. Evolutionary Programming with Non-Coding Segments for Real-valued Function Optimization. In: Proc. of IEEE Intl. Conf. on Systems, Man and Cybernetics (SMC'99), 1999,4: 242~247
  • 6Ohkura K, Matsumura Y, Ueda K. Robust Evolution Strategies.Applied Intelligence, Kluwer Academic Publishers, accepted for publication, 2002
  • 7Matsumura Y,Ohkura K,Ueda K. Evolutionary Dynamics of Evolutionary Programming in Noisy Environment. In: Proc. of Congress on Evolutionary Computation (CEC2001), 2001.17~24
  • 8Saravanan N,Fogel D B. Multi-Operator Evolutionary Programming: A Preliminary Study on Function Optimization. In: Proc. of the 6th Annual Conf. on Evolutionary Programming, Lecture Notes in Computer Science, Springer-Verlag, 1997,1213: 215 ~221
  • 9Wreenwood G G, Zhu Q J. Convergence in Evolutionary Programs with Self-Adaptation. Evolutionary Computation, MIT Press, 2002,2(11) :147~157
  • 10Rudolph G. Self-adaptation and Global Convergence: a Counterexample. In: Proc. of Cong. on Evol. Comp. 1999. 646~651

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部