Dynamic Diversity Population Based Flower Pollination Algorithm for Multimodal Optimization

被引:6
|
作者
Jeng-Shyang Pan [1 ]
Thi-Kien Dao [2 ]
Trong-The Nguyen [2 ]
Shu-Chuan Chu [3 ]
Tien-Szu Pan [2 ]
机构
[1] Fujian Univ Technol, Coll Informat Sci & Engn, Fuzhou, Peoples R China
[2] Natl Kaohsiung Univ Appl Sci, Dept Elect Engn, Kaohsiung, Taiwan
[3] Flinders Univ S Australia, Sch Comp Sci Engn & Math, Adelaide, SA, Australia
来源
INTELLIGENT INFORMATION AND DATABASE SYSTEMS, ACIIDS 2016, PT I | 2016年 / 9621卷
关键词
Flower pollination algorithm; Dynamic diversity flower pollination algorithm; Multimodal optimization problems;
D O I
10.1007/978-3-662-49381-6_42
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Easy convergence to a local optimum, rather than global optimum could unexpectedly happen in practical multimodal optimization problems due to interference phenomena among physically constrained dimensions. In this paper, an altering strategy for dynamic diversity Flower pollination algorithm (FPA) is proposed for solving the multimodal optimization problems. In this proposed method, the population is divided into several small groups. Agents in these groups are exchanged frequently the evolved fitness information by using their own best historical information and the dynamic switching probability is to provide the diversity of searching process. A set of the benchmark functions is used to test the quality performance of the proposed method. The experimental result of the proposed method shows the better performance in comparison with others methods.
引用
收藏
页码:440 / 448
页数:9
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