Comparison of swarm intelligence algorithms for high dimensional optimization problems

• Main Authors: Bashath, Samar, Ismail, Amelia Ritahani
• Format: Article
• Language: English; English
• Published: Institute of Advanced Engineering and Science 2018
• Subjects: T Technology (General); T58.7 Production capacity. Manufacturing capacity
• Online Access: http://irep.iium.edu.my/65214/1/65214_Comparison%20of%20swarm%20intelligence%20algorithms%20for%20high%20dimensional%20optimization%20problems.pdf; http://irep.iium.edu.my/65214/2/65214_Comparison%20of%20swarm%20intelligence%20algorithms%20for%20high%20dimensional%20optimization%20problems_SCOPUS.pdf; http://irep.iium.edu.my/65214/; http://www.iaescore.com/journals/index.php/IJEECS/article/view/10622/8786

High dimensional optimization considers being one of the most challenges that face the algorithms for finding an optimal solution for real-world problems. These problems have been appeared in diverse practical fields including business and industries. Within a huge number of algorithms, selecting one algorithm among others for solving the high dimensional optimization problem is not an easily accomplished task. This paper presents a comprehensive study of two swarm intelligence based algorithms: 1- particle swarm optimization (PSO), 2-cuckoo search (CS).The two algorithms are analyzed and compared for problems consisting of high dimensions in respect of solution accuracy, and runtime performance by various classes of benchmark functions.