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Faculty Dr Pratik Roy

Dr Pratik Roy

Assistant Professor

Department of Computer Science and Engineering

Contact Details

pratik.r@srmap.edu.in

Office Location

C V Raman Block, Level 2, Cabin No: 12

Education

2020
University of Calcutta
India
2010
MSc
Vidyasagar University
India
2008
BSc
University of North Bengal
India

Experience

  • May 2011 to October 2013 – JRF of CSIR – Siliguri Institute of Technology, Siliguri, West Bengal, India
  • August 2014 to January 2015 – Guest Lecturer – Ananda Chandra College, Jalpaiguri, West Bengal, India
  • October 2015 to April 2018 – SRF of CSIR – University of Calcutta, Kolkata, West Bengal, India
  • September 2018 to May 2019 – Guest Lecturer – New Alipore College, Kolkata, West Bengal, India
  • June 2019 to July 2021 – Assistant Professor – Techno India University, Kolkata, India
  • August 2021 to December 2022 – Assistant Professor – GLA University, Mathura, Uttar Pradesh, India

Research Interest

  • Prediction of Software Reliability using Machine Learning Techniques
  • Multi-objective reliability redundancy allocation optimization under uncertainty with novel evolutionary algorithms

Awards

  • 2011 – JRF – CSIR
  • 2015 – SRF - CSIR

Memberships

  • Member of IEEE

Publications

  • Optimization of time-dependent fuzzy multi-objective reliability redundancy allocation problem for n-stage series–parallel system

    Dr Pratik Roy, Satyajit De., Siddhartha Roy., Anil Bikash Chowdhury

    Source Title: Innovations in Systems and Software Engineering, Quartile: Q2, DOI Link

    View abstract ⏷

    This study introduces a time-dependent fuzzy multi-objective reliability redundancy allocation problem (TF-MORRAP) for the n-stage (level) series–parallel system. System reliability maximization and system cost minimization according to time by optimizing the redundant components counting at every stage of the system is the main objective of this study. This optimization is done by satisfying the entropy constraints with limited redundant components at every stage and in the whole system. The reliability and cost of every component are represented as triangular fuzzy numbers (TFN) to handle the uncertainty of input information of the system. According to time, the component reliability and cost decrease by some factor of their previous existing value. This factor follows the change in the length of radius of the inverse logarithmic spiral with respect to angle which is regarded as time here. The proposed problem is analyzed by using an over-speed protection system of a gas turbine. We compare the membership values of optimal solutions obtained by using two well-known techniques namely non-dominated sorting genetic algorithm-II (NSGA-II) and a multi-objective particle swarm optimization algorithm called NF-MOPSO. Various performances of the algorithms are compared to solve the aforementioned problem by using some performance metrics. NF-MOPSO shows the high satisfaction level of objective functions and better performance than NSGA-II.

Patents

Projects

Scholars

Interests

  • Artificial Intelligence
  • Deep Learning
  • Machine Learning
  • Software Engineering

Thought Leaderships

There are no Thought Leaderships associated with this faculty.

Top Achievements

Education
2008
BSc
University of North Bengal
India
2010
MSc
Vidyasagar University
India
2020
University of Calcutta
India
Experience
  • May 2011 to October 2013 – JRF of CSIR – Siliguri Institute of Technology, Siliguri, West Bengal, India
  • August 2014 to January 2015 – Guest Lecturer – Ananda Chandra College, Jalpaiguri, West Bengal, India
  • October 2015 to April 2018 – SRF of CSIR – University of Calcutta, Kolkata, West Bengal, India
  • September 2018 to May 2019 – Guest Lecturer – New Alipore College, Kolkata, West Bengal, India
  • June 2019 to July 2021 – Assistant Professor – Techno India University, Kolkata, India
  • August 2021 to December 2022 – Assistant Professor – GLA University, Mathura, Uttar Pradesh, India
Research Interests
  • Prediction of Software Reliability using Machine Learning Techniques
  • Multi-objective reliability redundancy allocation optimization under uncertainty with novel evolutionary algorithms
Awards & Fellowships
  • 2011 – JRF – CSIR
  • 2015 – SRF - CSIR
Memberships
  • Member of IEEE
Publications
  • Optimization of time-dependent fuzzy multi-objective reliability redundancy allocation problem for n-stage series–parallel system

    Dr Pratik Roy, Satyajit De., Siddhartha Roy., Anil Bikash Chowdhury

    Source Title: Innovations in Systems and Software Engineering, Quartile: Q2, DOI Link

    View abstract ⏷

    This study introduces a time-dependent fuzzy multi-objective reliability redundancy allocation problem (TF-MORRAP) for the n-stage (level) series–parallel system. System reliability maximization and system cost minimization according to time by optimizing the redundant components counting at every stage of the system is the main objective of this study. This optimization is done by satisfying the entropy constraints with limited redundant components at every stage and in the whole system. The reliability and cost of every component are represented as triangular fuzzy numbers (TFN) to handle the uncertainty of input information of the system. According to time, the component reliability and cost decrease by some factor of their previous existing value. This factor follows the change in the length of radius of the inverse logarithmic spiral with respect to angle which is regarded as time here. The proposed problem is analyzed by using an over-speed protection system of a gas turbine. We compare the membership values of optimal solutions obtained by using two well-known techniques namely non-dominated sorting genetic algorithm-II (NSGA-II) and a multi-objective particle swarm optimization algorithm called NF-MOPSO. Various performances of the algorithms are compared to solve the aforementioned problem by using some performance metrics. NF-MOPSO shows the high satisfaction level of objective functions and better performance than NSGA-II.
Contact Details

pratik.r@srmap.edu.in

Scholars
Interests

  • Artificial Intelligence
  • Deep Learning
  • Machine Learning
  • Software Engineering

Education
2008
BSc
University of North Bengal
India
2010
MSc
Vidyasagar University
India
2020
University of Calcutta
India
Experience
  • May 2011 to October 2013 – JRF of CSIR – Siliguri Institute of Technology, Siliguri, West Bengal, India
  • August 2014 to January 2015 – Guest Lecturer – Ananda Chandra College, Jalpaiguri, West Bengal, India
  • October 2015 to April 2018 – SRF of CSIR – University of Calcutta, Kolkata, West Bengal, India
  • September 2018 to May 2019 – Guest Lecturer – New Alipore College, Kolkata, West Bengal, India
  • June 2019 to July 2021 – Assistant Professor – Techno India University, Kolkata, India
  • August 2021 to December 2022 – Assistant Professor – GLA University, Mathura, Uttar Pradesh, India
Research Interests
  • Prediction of Software Reliability using Machine Learning Techniques
  • Multi-objective reliability redundancy allocation optimization under uncertainty with novel evolutionary algorithms
Awards & Fellowships
  • 2011 – JRF – CSIR
  • 2015 – SRF - CSIR
Memberships
  • Member of IEEE
Publications
  • Optimization of time-dependent fuzzy multi-objective reliability redundancy allocation problem for n-stage series–parallel system

    Dr Pratik Roy, Satyajit De., Siddhartha Roy., Anil Bikash Chowdhury

    Source Title: Innovations in Systems and Software Engineering, Quartile: Q2, DOI Link

    View abstract ⏷

    This study introduces a time-dependent fuzzy multi-objective reliability redundancy allocation problem (TF-MORRAP) for the n-stage (level) series–parallel system. System reliability maximization and system cost minimization according to time by optimizing the redundant components counting at every stage of the system is the main objective of this study. This optimization is done by satisfying the entropy constraints with limited redundant components at every stage and in the whole system. The reliability and cost of every component are represented as triangular fuzzy numbers (TFN) to handle the uncertainty of input information of the system. According to time, the component reliability and cost decrease by some factor of their previous existing value. This factor follows the change in the length of radius of the inverse logarithmic spiral with respect to angle which is regarded as time here. The proposed problem is analyzed by using an over-speed protection system of a gas turbine. We compare the membership values of optimal solutions obtained by using two well-known techniques namely non-dominated sorting genetic algorithm-II (NSGA-II) and a multi-objective particle swarm optimization algorithm called NF-MOPSO. Various performances of the algorithms are compared to solve the aforementioned problem by using some performance metrics. NF-MOPSO shows the high satisfaction level of objective functions and better performance than NSGA-II.
Contact Details

pratik.r@srmap.edu.in

Scholars