International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | Multi-Objective Genetic Algorithm to Enhance the Clustering Problems |
|---|---|
| ABSTRACT | Clustering is a key technique in data analysis used to group similar data points for better interpretation and decision-making. Traditional methods such as K-means clustering are widely applied due to their simplicity and efficiency; however, they often face limitations when dealing with complex datasets and multi-objective requirements. These methods typically optimize a single objective and are sensitive to initial conditions, which may lead to suboptimal results.To overcome these challenges, this work proposes a multi-objective clustering approach using the Non-dominated Sorting Genetic Algorithm II (NSGA-II). The clustering problem is formulated to simultaneously optimize objectives such as minimizing intra-cluster distance and maximizing inter-cluster separation. NSGA-II effectively explores the search space and generates a diverse set of Pareto-optimal solutions, enabling better trade-offs between conflicting objectives.The performance of the proposed approach is evaluated against the traditional K-Means algorithm. Experimental results demonstrate that the NSGA-II-based method achieves improved clustering quality, greater solution diversity, and enhanced robustness. This highlights the effectiveness of evolutionary multi-objective optimization techniques for solving complex clustering problems in real-world applications. |
| AUTHOR | CHEEKATI SANJAY GOUD, MARYALA HARSHITHA, VEDAVATHI.K, DR.V. SUBBARAMAIAH, DR.K. RAJITHA Student, Department of Computer Science and Engineering, Mahatma Gandhi Institute of Technology, Gandipet, India Assistant Professor, Department of Computer Science and Engineering, Mahatma Gandhi Institute of Technology, Gandipet, India |
| VOLUME | 183 |
| DOI | DOI: 10.15680/IJIRCCE.2026.1404087 |
| pdf/87_Multi-Objective Genetic Algorithm to Enhance the Clustering Problems.pdf | |
| KEYWORDS | |
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