Novel Immune Optimization Based on Lifespan Mechanism for Global Numerical Optimization Problems
In order to exploit and preserve the diversity of immune optimization algorithm when solving high dimensional global optimization problems, a novel immune optimization algorithm based lifespan (LIO) model is proposed. LIO incorporates a lifespan model, local and global search procedure to improve the overall performance in solving global optimization instance. Particularly, a novel performance evaluation criterion is constructed in this paper, by which the performance of different population-based algorithms can be compared easily. In the experimental study, firstly several conventional benchmarks are used to determine the values of parameters. Next, the presented LIO is compared with several population-based algorithms. The experimental results of the LIO are significantly better than that of the conventional clonal selection algorithm (CSA) in terms of the performance evaluation criterion proposed.
Artificial immune systems evolutionary algorithm immune optimization global Optimization
Yuzhen Liu Shoufu Li
School of Mathematics and computational science Xiangtan University Xiangtan, Hunan,China P.R.Colleg School of Mathematics and computational science Xiangtan University Xiangtan, Hunan,China P.R.
国际会议
厦门
英文
132-136
2010-10-29（万方平台首次上网日期，不代表论文的发表时间）