Comprehensive learning pigeon-inspired optimization with tabu list

作     者：Shang XIANG Lining XING Ling WANG Kai ZOU 

作者机构：College of Systems Engineering National University of Defense Technology College of Engineering Shanghai Polytechnic University Department of Automation Tsinghua University School of Public Administration Xiangtan University 

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：99-101页

核心收录：

学科分类：0808[工学-电气工程] 08[工学] 081104[工学-模式识别与智能系统] 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 Natural Science Fundation for Distinguished Young Scholars of China (Grant No. 61525304) National Natural Science Foundation of China (Grant Nos. 61773120, 61873328) Hunan Postgraduate Research Innovation Project of China (Grant No. CX2018B022) Foundation for the Author of National Excellent Doctoral Dissertation of China (Grant No. 2014-92) 

主　　题：pro Comprehensive learning pigeon-inspired optimization with tabu list 

摘      要：Dear editor,During the last decade, population-based algorithms have been extensively used to solve multimodal, discontinuous, non-convex, and nondifferentiable optimization problems. These algorithms search for the best solution by applying some operators and strategies over a set (population) of potential solutions (individuals). All those operators or strategies follow one principle:balancing