FUZZY GENETIC ALGORITHMS BASED ON FUZZY NUMBER CODING ON [0,1] AND ITS APPLICATION

被引：0
作者：
Wang, Shu-Tian [1 ]
Li, Zi-Fang [2 ]
Zhang, Zhi-Jun [3 ]
Jin, Chen-Xia [4 ]
机构：
[1] Hebei Inst Ind Technol, Dept Basic Sci, Shijiazhuang 050091, Peoples R China
[2] Hebei Univ Econ & Bussiness, Sch Math & Stat, Shijiazhuang 050061, Peoples R China
[3] Inst Chem Def, dept Fdn, Beijing 102205, Peoples R China
[4] Hebei Univ Sci & Technol, Sch Econ & Management, Shijiazhuang 050018, Peoples R China
来源：
PROCEEDINGS OF 2009 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-6 | 2009年
基金：
中国国家自然科学基金;
关键词：
Fuzzy optimization; Genetic algorithms; Decentralization degree; Compound mutation;
D O I：
10.1109/ICMLC.2009.5212102
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
An improved genetic algorithm for fuzzy programming problems with triangular fuzzy variables is proposed in this paper. The decentralization degree of fuzzy numbers is defined, and the way of coding triangular fuzzy number on [0, 1] is built. So we can limit the type of fuzzy numbers, increase the convergence property of algorithm, and make the fuzzy information processing more reasonable. Based on the structure characteristics of optimization variables, the crossover operation was replaced by linear recombination, and a compound mutation operation to triangular fuzzy numbers is given. The effectiveness and usefulness are discussed through an example in the end.
引用
收藏
页码：2564 / +
页数：3
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