Shweta Rana

Institute of Technology Management

Papers

1

Total Citations

6

H-Index

1

About

Shweta Rana is a computer science researcher whose work focuses on tackling computationally intractable problems, particularly the Travelling Salesman Problem (TSP)—a classic NP-Complete challenge with broad applications in science and engineering. Her most cited paper, "Solving Travelling Salesman Problem Using Improved Genetic Algorithm" (2017), introduces a novel optimization approach that enhances traditional genetic algorithms to more effectively navigate the complex solution space of TSP. This work addresses one of the hardest problems in computer science, where conventional algorithms fall short, by leveraging evolutionary computation to find near-optimal solutions efficiently. With 6 citations, her contribution provides a practical pathway for researchers and engineers dealing with routing, logistics, and network design challenges. Rana’s research underscores the importance of heuristic and metaheuristic methods in overcoming the limitations of exact algorithms for NP-Complete problems, making her work valuable for students and practitioners exploring advanced optimization techniques in artificial intelligence and operations research.

Research Focus

Key Achievements

1
H-Index
1
Papers
6
Total Citations
6
Avg Citations/Paper
🏆 Most Cited Paper
Solving Travelling Salesman Problem Using Improved Genetic Algorithm
6 citations · 2017
📈 Most Prolific Year: 2017 (1 Papers)
🤝 Key Collaborators: 1
🏛 Institutions: Institute of Technology Management

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago