Heterogeneous pigeon-inspired optimization

作     者：Hao WANG Zhuxi ZHANG Zhen DAI Jun CHEN Xi ZHU Wenbo DU Xianbin CAO 

作者机构：School of Electronic and Information Engineering Frontier Institute of Science and Technology InnovationBeihang University School of Engineering and Materials Science Queen Mary University of London 

出 版 物：《Science China(Information Sciences)》 (中国科学:信息科学(英文版))

年 卷 期：2019年第62卷第7期

页      面：64-72页

核心收录：

学科分类：0810[工学-信息与通信工程] 12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 0808[工学-电气工程] 081104[工学-模式识别与智能系统] 08[工学] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by National Key Research and Development Program of China (Grant No. 2016YFB1200100) National Natural Science Foundation of China (Grant Nos. 61425014, 61521091, 91538204, 61671031, 61722102) 

主　　题：heuristic optimization pigeon-inspired optimization particle heterogeneity network-based topology scale-free network selective-informed learning 

摘      要：Pigeon-inspired optimization(PIO) is a swarm intelligence optimizer inspired by the homing behavior of pigeons. PIO consists of two optimization stages which employ the map and compass operator,and the landmark operator, respectively. In canonical PIO, these two operators treat every bird equally,which deviates from the fact that birds usually act heterogenous roles in nature. In this paper, we propose a new variant of PIO algorithm considering bird heterogeneity — HPIO. Both of the two operators are improved through dividing the birds into hub and non-hub roles. By dividing the birds into two groups, these two groups of birds are respectively assigned with different functions of exploitation and exploration, so that they can closely interact with each other to locate the best promising solution. Extensive experimental studies illustrate that the bird heterogeneity produced by our algorithm can benefit the information exchange between birds so that the proposed PIO variant significantly outperforms the canonical PIO.