Comparison of Swarm Intelligence Algorithms for High Dimensional Optimization Problem

Samar Bashath, Amelia Ritahani Ismail

Abstract


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

 


Keywords


: high dimensional problem swarm intelligence algorithms, particle swarm optimization, cuckoo search



DOI: http://doi.org/10.11591/ijeecs.v11.i1.pp%25p
Total views : 9 times

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

shopify stats IJEECS visitor statistics