Improvement on boundary searching of Accelerating Genetic Algorithm

摘要：

Accelerating Genetic Algorithm (AGA)’s disadvantages of unable to search the optimal solution when the solution is in the boundary of feasible region was proved through theoretical analysis and numerical experimentation. The solution of adding random individuals whose variable obeying to saddle distribution into initial population to increase the ability of searching the optimal solution in the boundary of AGA was proposed. The results of numerical tests show that the introduction of special individuals obeying to triangular distribution or pulse distribution can increase the accuracy by 3~10 times and convergence probability by 10％~20％ when the global optimal solution is near the boundaries of feasible region and the accuracy is increased by 3~7 times and convergence probability by 25％~50％ when global optimum is in the boundary of feasible region.

关键词： Accelerating Genetic Algorithm Boundary Searching Numerical experimentation

作者: XU Bin ZHONG Ping-an TANG Lin

作者单位: College of Hydrology and Water ResourcesHohai University.Nanjing, China Yellow River Engineering Consulting Co.,Ltd Yellow River Conservancy Commission Zhengzhou, China

会议类型: 国际会议

会议名称: 2012 International Conference on Intelligent System Design and Engineering Applications(2012年智能系统设计与工程应用国际会议 ISDEA 2012)

会议地点: 三亚

会议语种:英文

页码: 301-305

在线出版日期: 2012-01-06（万方平台首次上网日期，不代表论文的发表时间）