桂林电子科技大学学报2017，Vol.37Issue(3)：254-258,5.
基于改进小生境遗传算法的三角模糊数互补判断矩阵排序方法
Priority method of triangular fuzzy number complementary judgment matrix based on improved niche genetic algorithm
摘要
Abstract
A TFN sorting method based on improved niche genetic algorithm (NGA) is proposed to solve the problem of long computation time in TFN (triangular fuzzy number complementary judgment matrix).The TFN ranking method is used to set up the optimization model to satisfy the consistency test,the matrix element adjustment and the weight order as the optimization target,and to minimize the initial judgment matrix under the condition that the TFN has satisfactory consistency.The NGA is improved by introducing the concept of niche entropy to measure the population diversity.The part of the evolutionary parameters in the improved NGA is adjusted adaptively according to the niche entropy,and the efficiency of the algorithm is improved.The simulation results show that the improved NGA can improve the operation efficiency and the stability of computation.关键词
三角模糊数互补判断矩阵/改进小生境遗传算法/运算效率Key words
triangular fuzzy number complementary judgment matrix/improved niche genetic algorithm/operation efficiency分类
自科综合引用本文复制引用
杨雪康,匡兵,林瑞,周峰..基于改进小生境遗传算法的三角模糊数互补判断矩阵排序方法[J].桂林电子科技大学学报,2017,37(3):254-258,5.基金项目
国家自然科学基金(51265006) （51265006）
