Non-dominated rank based sorting genetic algorithms

被引：2
|
作者：
Ghosh, Ashish [1 ]
Das, Mrinal Kanti [2 ]
机构：
[1] Indian Stat Inst, Machine Intelligence Unit, Kolkata 700108, India
[2] Indian Inst Sci, Bangalore 560012, Karnataka, India
来源：
FUNDAMENTA INFORMATICAE | 2008年 / 83卷 / 03期
关键词：
multi-objective optimization; evolutionary computing; genetic algorithms; Pareto optimality;
D O I：
暂无
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
In this paper a new concept of ranking among the solutions of the same front, along with elite preservation mechanism and ensuring diversity through the nearest neighbor method is proposed for multi-objective genetic algorithms. This algorithm is applied on a set of benchmark multi-objective test problems and the results are compared with that of NSGA-II (a similar algorithm). The proposed algorithm is seen to over perform the existing algorithm. More specifically, the new approach has been used to solve the deceptive multi-objective optimization problems in a better way.
引用
收藏
页码：231 / 252
页数：22
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