Dr. Anand Kumar
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Dr. Anand Kumar

Professor
M.S. Engineering College, India

Highest Degree
Ph.D. in Computer Science from Saurashtra University, Gujarat State, India

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Biography

Dr. Anand Kumar is currently working as Dean-Academics, Professor & Head in Department of MCA and Professor in Department of Computer Science & Engineering at MS Engineering College, Karnataka, India. He obtained his PhD in Computer Science from Department of Computer Science, Saurashtra University, Rajkot in June 2011. He has more than fourteen years of teaching experience. He also worked with AMC Engineering College Bangalore and CPPGICA Gujarat University Ahmedabad. His research interests include Evolutionary Computing, Genetic Algorithms, Data Analytics, Software Project Management, Cryptography& Network Security and Network Design. He has authored 23 research papers in international journal and international - national conferences. At present 06 students are registered for PhD program under his supervision. He also serves the editorial board of many reputed international journals. He is member of Technical Program Committee of IEEE and actively associated with several international organization.

Area of Interest:

Computer Sciences
100%
Evolutionary Computing
62%
Genetic Algorithm
90%
Network Design
75%
Optimization
55%

Research Publications in Numbers

Books
1
Chapters
0
Articles
18
Abstracts
1

Selected Publications

  1. Kalaiselvi, K. and A. Kumar, 2017. Effect of variations in the population size and generations of genetic algorithms in cryptography-an empirical study. Indian J. Sci. Technol., Vol. 10. 10.17485/ijst/2017/v10i19/110803.
    CrossRef  |  
  2. Kumar, A., 2016. Network Design Using Genetic Algorithm. LAP Lambert Academic Publishing, Germany, ISBN: 978-3-659-89835-8, Pages: 256.
  3. Kumar, A. and S.T. Krishna, 2015. Network route optimization. Int. J. Appl. Eng. Res., 10: 38769-38773.
  4. Kumar, A. and S.T. Krishna, 2015. An evolutionary approach to solve network route optimization problem. Indian J. Sci. Technol., Vol. 8. .
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  5. KalaiSelvi, K. and A. Kumar, 2014. Conventional cryptography and evolutionary approach. Global J. Comput. Intel. Res., 4: 1-8.
  6. Kumar, A. and N.N. Jani, 2012. An influence of chromosomes population in degree constraint minimal spanning tree problem using evolutionary approach genetic algorithm. J. Comput. Intell. Bioinf., 5: 45-56.
  7. Kumar, A. and N.N. Jani, 2012. An empirical study on crossover operator for degree constraint minimal spanning tree problem using genetic algorithm. Int. J. Comput. Intell. Res., 8: 1-15.
  8. Kumar, A. and N.N. Jani, 2010. Network design problem using genetic algorithm: An empirical study on selection operator. Int. J. Comput. Sci. Appli., 3: 48-52.
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  9. Kumar, A. and N.N. Jani, 2010. Network design problem using genetic algorithm-an empirical study on mutation operator. Int. J. Soft Comput., 5: 171-176.
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  10. Kumar, A. and N.N. Jani, 2010. Network design problem using genetic algorithm-an empirical study on mutation operator. Global J. Comput. Sci. Technol., 10: 77-82.
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  11. Kumar, A. and N.N. Jani, 2010. Genetic algorithm for network design problem-An empirical study of crossover operator with generation and population variation. Int. J. Inform. Technol. Knowledge Manage., 2: 605-611.
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  12. Kumar, A. and N.N. Jani, 2010. An evolutionary approach to allocate frequency in cellular telephone system. Int. J. Comput. Appl., 1: 86-90.
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  13. Kumar, A. and N.N. Jani, 2010. An evolutionary approach for shortest path problem-courier delivery system. Int. J. Comput. Intell. Res., 6: 261-273.
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  14. Kumar, A. and N.N. Jani, 2010. An algorithm to detect cycle in an undirected graph. Int. J. Comput. Intell. Res., 6: 305-310.
  15. Kumar, A. and N.N. Jani, 2010. A novel genetic algorithm approach for network design with robust fitness function. Int. J. Comput. Theory Eng. Singapore, 2: 459-465.
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  16. Kumar, A. and N.N. Jani, 2010. Genetic algorithm for network design problem: An empirical study of crossover operator with generation and population variation. Int. J. Inform. Technol. Knowledge Manage., 2: 605-611.
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  17. Kumar, A., 2009. Using a genetic algorithm approach to solve the chromatic number problem. Int. J. Comput. Sci. Appl., 2: 117-121.
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  18. Kumar, A., 2009. A nature based evolutionary approach to solve network communication NP-hard traveling salesman problem. Int. J. Comput. Intell. Res. Appl., 3: 27-32.
  19. Kumar, A., 2008. Map color problem using genetic approach. Proceedings of the 2nd National Conference on Challenges and Opportunities in Information Technology, March 29, 2008, RIMT-IET, Mandi Gobindgarh, India pp: 247-250.
  20. Kumar, A., 2008. Map color problem using a genetic algorithm approach. Int. J. Algorithms Comput. Mathe., 1: 1-6.