An improved krill herd algorithm: Krill herd with linear decreasing step

• Published in: Applied mathematics and computation Vol. 234; pp. 356 - 367
• Main Authors: Li, Junpeng, Tang, Yinggan, Hua, Changchun, Guan, Xinping
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 15.05.2014
• Subjects: Algorithms; Benchmarking; Exploration; Krill; Krill herd; Linear decreasing; Mathematical analysis; Mathematical models; Optimization; Swarm intelligent algorithms; Swarm intelligent algorithms; Krill herd; Linear decreasing; Optimization
• ISSN: 0096-3003; 1873-5649
• DOI: 10.1016/j.amc.2014.01.146

•A deficiency of KH is analyzed.•Why KH cannot achieve the excellent balance between exploration and exploitation in optimization processing is explained.•To overcome the defect, an improved KH with linear decreasing step (KHLD) is proposed. Krill herd (KH) inspired by the herding behavior of the krill individuals is a new swarm intelligent algorithm which is proved to perform better than other swarm intelligent algorithms. However, there are some weak points yet. In this paper, we analyze a deficiency of KH which cannot achieve the excellent balance between exploration and exploitation in optimization processing and proposed an improved KH-krill herd with linear decreasing step (KHLD). Twenty benchmark functions are used to verify the effectiveness of these improvements and it is illustrated that, in most cases, the performance of KHLD is superior to the standard KH.