文献类型：期刊文献

英文题名：An improved genetic algorithm encoded by adaptive degressive ary number

作者：Zhang, Yijie[1];Liu, Mandan[1]

机构：[1]East China Univ Sci & Technol, 130 Meilong Rd, Shanghai, Peoples R China

年份：2018

卷号：22

期号：20

起止页码：6861

外文期刊名：SOFT COMPUTING

收录：;EI(收录号：20175104563294);WOS:【SCI-EXPANDED(收录号:WOS:000445948700022)】；

语种：英文

外文关键词：Genetic algorithm; Encoding; Adaptive; Degressive ary number

摘要：Genetic algorithm (GA) is a random search algorithm, which has been commonly used to solve optimization problems. A new encoding method of GA, adaptive degressive ary number encoding, is proposed in this paper. This paper firstly introduces the N-ary encoding genetic algorithm and then defines the degressive ary number encoded genetic algorithm. Based on degressive ary number encoded genetic algorithm, this paper proposes a feasible adaptive change rule of the ary number encoding, which can change ary number with the fitness function's value. All the parameters are selected according to the parameters' experiments. The proposed algorithm is used to solve the function optimization problems to test the performance. The performances of the proposed algorithm are compared with GA, some classic algorithms and some latest algorithms. The experiments show that the improved adaptive degressive ary number encoded genetic algorithm has a better searching ability and a faster rate of convergence.