A modified particle swarm optimization algorithm for solving DNA problem
- Publication Type:
- Conference Proceeding
- 60th International Scientific Conference on Information Technology and Management Science of Riga Technical University, ITMS 2019 - Proceedings, 2019
- Issue Date:
Copyright Clearance Process
- Recently Added
- In Progress
- Open Access
This item is open access.
The embargo period expires on 26 Dec 2021
© 2019 IEEE. DNA Sequencing is a complex problem since DNA computation depends on the biochemical reactions of DNA molecules that resulted in an improper or unwanted results. Thus, researchers are focusing to make the molecular computation for the DNA sequences design problem more consistent. Designing of DNA sequencing consists of several difficult and inconsistent designing parameters and typical optimization approaches do not perform well. As a result, a Modified Particle Swarm Optimization Algorithm (MPSO) is proposed to elucidate this problem. Four objective functions that are continuity, similarity, hairpin, and H-measure are used to evaluate this multi-objective problem. Different methods are used to explain DNA problem but to solve it with MPSO the multi-objective problem is converted into a single-objective problem. MPSO is presented to minimize the objective functions subject to two constraints. Average and Standard deviation values of the objective functions are used to calculate the efficiency of the presented method. The results obtained are compared with the other approaches and it showed that MPSO gives better performance.
Please use this identifier to cite or link to this item: