Dr. Tamal Ghosh

Associate Professor at the Department of Computer Science & Engineering

Email: tamal.ghosh1@adamasuniversity.ac.in

Room No. 6205, 2nd Floor, School of Engineering and Technology, Adamas University

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Qualifications

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Teaching

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Research

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Research Interests:

  • Artificial Intelligence
  • Evolutionary Computing
  • Collaborative Machine Learning
  • Industry 4.0
  • Digital Twin
  • Publications

    Peer-reviewed Journals:

    SCI:

  • D Bhattacharjee, T Ghosh, P Bhola, K Martinsen and P Dan. (2021). Ecodesigning and improving performance of plugin hybrid electric vehicle in rolling terrain through multi-criteria optimisation of powertrain. Proc IMechE Part D: Journal of Automobile Engineering, 236(5), pp. 1019-1039, (Impact Factor 1.828)
  • T Ghosh and K Martinsen. (2021). A Collaborative Beetle Antennae Search Algorithm Using Memory Based Adaptive Learning. Applied Artificial Intelligence, 35(6), pp. 440-475, ISSN: 1087-6545. (Impact Factor 1.58)
  • T Ghosh, Y Wang, K Martinsen and K Wang. (2020). A Surrogate-Assisted Optimization Approach for Multi-Response End Milling of Aluminium Alloy AA3105, International Journal of Advanced Manufacturing Technology, 111, pp. 2419–2439, ISSN: 02683768 (Impact Factor 3.226)
  • T Ghosh, K Martinsen and PK Dan, (2019). Development and Correlation Analysis of Non-Dominated Sorting Buffalo Optimization NSBUF II Using Taguchi's Design Coupled Gray Relational Analysis and ANN, Applied Soft Computing, 85, 105809, ISSN: 1568-4946. (Impact Factor 6.725)
  • D Bhattecharjee, T Ghosh, P Bhola, K Martinsen and PK Dan, (2019). Data-Driven Surrogate Assisted Evolutionary Optimization of Hybrid Powertrain for Improved Fuel Economy and Performance, Energy, 183, pp. 235-248. ISSN: 0360-5442. (Impact Factor 8.857)
  • T Ghosh and K Martinsen. (2019). CFNN-PSO: An Iterative Predictive Model for Generic Parametric Design of Machining Processes, Applied Artificial Intelligence, 33(11), 951-978,ISSN: 1087-6545. (Impact Factor 1.58)
  • T Ghosh and K Martinsen. (2019). Generalized approach for multi-response machining process optimization using machine learning and evolutionary algorithms, Engineering Science and Technology, an International Journal. 23(3), pp. 650-663, ISSN 2215-0986. (Impact Factor: 6.39)
  • ​​T Ghosh, B Doloi and PK Dan. (2017). Utilization-based Grouping Efficiency and Multi Criteria Decision Approach in Designing Manufacturing Cells, Proceedings of the Institution of Mechanical Engineers, Part-B: Journal of Engineering Manufacture, 231(3), pp. 505-522. ISSN: 09544054. (Impact Factor 2.759)
  • T Ghosh, B Doloi and PK Dan. (2016). Applying soft-computing techniques in solving dynamic multi-objective layout problems in cellular manufacturing system, International Journal of Advanced Manufacturing Technology, 86(1), pp.237-257, ISSN: 02683768. (Impact Factor 3.226)
  • M Chattopadhyay, S Sengupta, T Ghosh, PK Dan and S Mazumdar. (2013). Neuro-Genetic Impact on Cell Formation Methods of Cellular Manufacturing System Design: A Quantitative Review and Analysis, Computers & Industrial Engineering, 64(1), pp. 256–272, ISSN: 03608352. (Impact Factor 5.431)
  • S Sengupta, T Ghosh and PK Dan. (2011). Fuzzy ART K-Means Clustering Technique: a hybrid neural network approach to cellular manufacturing systems, International Journal of Computer Integrated Manufacturing, 24(10), pp. 927-938, ISSN: 0951192X. (Impact Factor 3.70)
  • SCOPUS and Others:

  • T Ghosh and K Martinsen, (2020). Deploying NSBA algorithm for Bi-Objective Manufacturing Cells Considering Percentage Utilization of Machines, International Journal of Intelligent Systems, Technologies, and Applications, 19(3), pp. 257-279, ISSN: 1740-8865.
  • ​T Ghosh. (2020). Optimal design of manufacturing cells considering machine usage percentage, Journal of Advanced Manufacturing Systems, 19(3), pp. 411-423, ISSN: 1793-6896.
  • T Ghosh. (2019). Generalized Utilization-Based Similarity Coefficient For Machine-Part Grouping Problem In Cellular Manufacturing, Management and Production Engineering Review, 10(4), pp. 90-100, ISSN: 2080-8208.
  • T Ghosh, B Doloi and PK Dan. (2016). An Immune Genetic algorithm for inter-cell layout problem in cellular manufacturing system, Production Engineering, 10(2), pp.157-174, ISSN: 09446524.
  • T Ghosh, S Sengupta, B Doloi and PK Dan. (2014). AI-based techniques in cellular manufacturing systems: a chronological survey and analysis, International Journal of Industrial and Systems Engineering, 17(4), pp.449 – 476, ISSN: 17485037.
  • T Ghosh and PK Dan. (2012). Particle swarm optimisation in development of component families using classification and coding system: a case study in an Indian manufacturing firm, International Journal of Services and Operations Management, 13(4), pp. 441-456, ISSN: 1741539X.
  • T Ghosh, T Chakraborty and PK Dan. (2012). An Effective AHP-based Metaheuristic Approach to Solve Supplier Selection Problem, International Journal of Procurement Management, 5(2), pp. 140-159, ISSN: 17538432.
  • S Sengupta, T Ghosh and PK Dan. (2011). A Hybrid Neural Network Approach to Cell Formation in Cellular Manufacturing, International Journal of Intelligent Systems Technologies and Applications, 10(4), pp. 360-376, ISSN: 17408865.
  • T Ghosh, S Sengupta, M Chattopadhyay and PK Dan. (2011). Meta-heuristics in Cellular Manufacturing: A State-of-the-art Review, International Journal of Industrial Engineering Computations, 2(1), pp. 87-122, ISSN: 19232926.
  • T Ghosh, M Modak and PK Dan. (2011). SAPFOCS: a metaheuristic based approach to part family formation problems in group technology, International journal of management science and engineering management, 6(3), 231-240.
  • T Ghosh and K Martinsen, (2020). Deep-Learning Assisted Iterative Multi-Objective Optimization of Yarn Production Process, International Journal of Experimental Design and Process Optimisation, 6(3), pp. 234 - 252, ISSN: 2040-2252.
  • T Ghosh, PK Dan and M Chattopadhyay. (2013). Hybrid Principal Component Analysis Technique to Machine-Part Grouping Problem in Cellular Manufacturing System, International Journal of Advanced Operations Management, 5(3), pp.237 – 260, ISSN: 1758938X.
  • T Ghosh and PK Dan. (2011). Effective Clustering Method for Group Technology Problems: A Short Communication, E-Journal of Science & Technology, 6(4), 23-28.
  • T Ghosh, S Sengupta and PK Dan. (2010). A hybrid heuristic based clustering algorithm to design manufacturing cell, Management and Production Engineering Review, 1(4), 26-37. ISSN: 2080-8208.
  • T Chakraborty, T Ghosh and PK Dan. (2010). Application of analytic hierarchy process and heuristic algorithm in solving vendor selection problem, Business Intelligence Journal, 4(1), 167-177. ISSN 1918-2325.
  • Peer-reviewed Conferences:

    Scopus Indexed International Conferences:

  • T Ghosh. (2022). An Industrial Application of Cellular Manufacturing Using African Buffalo Optimization, IWAMA 2021, Shanghai, China, LNEE 80, pp. 1-7, Springer.
  • Y Kaushik and T Ghosh. (2022). PSO-Based Improved Surface Roughness Measuring Approach of Manufactured Product Within CP Factory Using T6 6068 Aluminium, ICICT 2022, London, UK. LNNS Vol. 465, pp. 163-172, Springer.
  • T Ghosh and K Martinsen. (2020). NSGA III for CNC End Milling Process Optimization, SoMMA 2019, Trivandrum, India, Communications in Computer and Information Science (CCIS), Springer, Vol. 1203, 2020.
  • B. Chen, K. Wang, X. Gao, Y. Wang, S. Chen, T. Zhang, K. Martinsen and T. Ghosh. (2020). A New Fault Identification Method Based on Combined Reconstruction Contribution Plot and Structured Residual, IWAMA 2019. Plymouth UK. Lecture Notes in Electrical Engineering (LNEE), Springer, vol. 634.
  • X. Gao, S. Chen, K. Wang, Y. Wang, W. Xie, J. Yuan, K. Martinsen and T. Ghosh. (2020). Collaborative Fault Diagnosis Decision Fusion Algorithm Based on Improved DS Evidence Theory, IWAMA 2019. Plymouth, UK. Lecture Notes in Electrical Engineering (LNEE), Springer, vol. 634.
  • T Ghosh and K Martinsen. (2020). Machine Learning based Heuristic Technique for Multi-Response Machining Process, IIRTS 2019, Krakow, Poland. Lecture notes in Mechanical Engineering (LNME), Springer.
  • T Ghosh, K Martinsen and PK Dan. (2019). Data-Driven Beetle Antennae Search Algorithm for Electrical Power Modeling of a Combined Cycle Power Plant. WCGO 2019, Metz, France. Advances in Intelligent Systems and Computing (AISC), Springer, pp. 906-915. ​​
  • National Conferences:

  • D Ghosh, T Ghosh, B Doloi and P Das. (2015). Optimization of Influential Process Parameters of Abrasive Waterjet Cutting of Glass, International Conference on Precision, Meso, Micro and Nano Engineering (COPEN-9), IIT Bombay, 10th – 12th December, 2015.
  • T Ghosh, B Doloi and PK Dan. (2014). A Novel Cell Formation Technique in Cellular Manufacturing System Based on Various Production Factors, 5thInternational & 26th All India Manufacturing Technology Design and Research Conference (AIMTDR-2014), IIT Guwahati, India, 12th-14th December, 2014.
  • T Ghosh and PK Dan. (2012). Modeling of Optimal Design of Manufacturing Cell Layout Considering Material Flow and Closeness Rating Factors, 4thInternational & 25th All India Manufacturing Technology Design and Research Conference (AIMTDR-2012), Jadavpur University, India, 14th-16th December, 2012.

  • T Ghosh and PK Dan. (2011). An Effective Machine-Part Grouping Algorithm to Construct Manufacturing Cells, National Conference on Industrial Engineering, In Proceedings of Conference on Industrial Engineering (NCIE 2011), WBUT Kolkata, India, 17th-18th February, 2011.
  • S Sengupta, T Ghosh, PK Dan and M Chattopadhyay. (2011). Hybrid fuzzy-art based k-means clustering methodology to cellular manufacturing using operational time, International Conference on Operational Excellence for Global Competitiveness (ICOEGC 2011), RVCE Bangalore, India, 3rd–5th February, 2011.
  • Book Chapters:

  • PK Dan, T Ghosh and S Sengupta. (2012). Application of Soft-Computing Methods in Cellular Manufacturing, DP Davim (Ed.), Computational Methods for Optimizing Manufacturing Technology: Models and Techniques, IGI-Global, Hershey, PA, USA, pp. 1-43, 2012, ISBN: 9781466601284.
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