Chaotic Immune Symbiotic Organisms Search algorithm for solving optimisation problem
Achieving an optimal solution is very crucial while solving a problem. To achieve the optimality required, optimisation techniques can be implemented while solving the problem. The presence of classical optimisation techniques has enabled an optimal solution to be obtained. However, as the complexit...
Saved in:
| Main Authors: | , , , |
|---|---|
| Other Authors: | |
| Format: | Article |
| Published: |
Science Publishing Corporation Inc
2023
|
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Universiti Tenaga Nasional |
| Summary: | Achieving an optimal solution is very crucial while solving a problem. To achieve the optimality required, optimisation techniques can be implemented while solving the problem. The presence of classical optimisation techniques has enabled an optimal solution to be obtained. However, as the complexity of the optimisation problem increased, classical optimisation techniques faced difficulties in providing optimal solutions. Heuristics-based algorithms were introduced to counter the problem faced by classical optimisation techniques. Good performance of these heuristics-based algorithm has been implied through various implementation in solving optimisation problems. Despite the performance of these algorithms, the flaws of these algorithms hinder them from producing high-quality results. To mitigate the problem, this paper presents the development of Chaotic Immune Symbiotic Organisms Search algorithm which was inspired by the element of diversification as well as the increased capability of exploration. The performance of the proposed algorithm has been tested by solving several benchmark test functions. A comparative study was also conducted with respect to several other existing optimisation algorithms resulted in the superiority of the proposed algorithm in providing high-quality solutions. � 2018 Authors. |
|---|