Dr. SHUBHAM GUPTA


Dr. SHUBHAM GUPTA

Assistant Professor
Department of Mathematics
Motilal Nehru National Institute of Technology Allahabad, Prayagraj, India-211004
E-mail: shubham.gupta[at]mnnit[dot]ac[dot]in
Telephone: +91 9520458076(O) +91 9520458076(M)

Research Publications


Journals:

Gupta, S., & Deep, K. (2018). “Cauchy grey wolf optimiser for continuous optimisation problems”. Journal of Experimental & Theoretical Artificial Intelligence, Vol. 30, pages 1051-1075, DOI: https://doi.org /10.1080/0952813X.2018.1513080. (SCIE, Q2, IF: 1.7)
Gupta, S., & Deep, K. (2018). “Random walk grey wolf optimizer for constrained engineering optimization problems”. Computational Intelligence, Vol. 34, pages 1025-1045, DOI: https://doi.org/10.1111/coi n.12160. (SCIE, Q2, IF: 1.7)
Gupta, S., & Deep, K. (2019). “An efficient grey wolf optimizer with opposition-based learning and chaotic local search for integer and mixed-integer optimization problems”. Arabian Journal for Science and Engineering, Vol. 44, pages 7277–7296, DOI: https://doi.org/10.1007/s13369-019-03806w. (SCIE, Q1, IF: 2.9)
Gupta, S., & Deep, K. (2019). “An opposition-based chaotic grey wolf optimizer for global optimisation tasks”. Journal of Experimental & Theoretical Artificial Intelligence, Vol. 31, pages 751-779, DOI: https://doi.org/10.1080/0952813X.2018.1554712. (SCIE, Q2, IF: 1.7)
Gupta, S., & Deep, K. (2019). “Enhanced leadership-inspired grey wolf optimizer for global optimization problems”. Engineering with Computers, Vol. 36, pages 1777–1800, DOI: https://doi.org/10.1007/s0 0366-019-00795-0. (SCIE, Q1, IF: 4.9)
Gupta, S., & Deep, K. (2019). “Improved sine cosine algorithm with crossover scheme for global optimization”. Knowledge-Based Systems, Vol. 165, pages 374-406, DOI: https://doi.org/10.1016/j.knosys.2018.12.0 08. (SCI, Q1, IF: 7.6)
Gupta, S., & Deep, K. (2019). “A hybrid self-adaptive sine cosine algorithm with opposition based learning”. Expert Systems with Applications, Vol. 119, pages 210-230, DOI: https://doi.org/10.1016/j.eswa.2018. 10.050. (SCIE, Q1, IF: 7.5)
Gupta, S., & Deep, K. (2019). “A novel random walk grey wolf optimizer”. Swarm and evolutionary computation, Vol. 44, pages 101-112, DOI: https://doi.org/10.1016/j.swevo.2018.01.001. (SCIE, Q1, IF: 8.5)
Gupta, S., &Deep, K.(2020). “Optimal coordination of overcurrent relays using improved leadershipbased grey wolf optimizer”. Arabian Journal for Science and Engineering, Vol. 45, pages 2081-2091, DOI: https://doi.org/10.1007/s13369-019-04025-z. (SCIE, Q1, IF: 2.9)
Gupta, S., & Deep, K. (2020). “A novel hybrid sine cosine algorithm for global optimization and its application to train multilayer perceptrons”. Applied Intelligence, Vol. 50, pages 993-1026, DOI: https://doi.org/10.1007/s10489-019-01570-w. (SCI, Q2, IF: 3.5)
Lei, Z., Gao, S., Gupta, S., Cheng, J., & Yang, G. (2020). “An aggregative learning gravitational search algorithm with self-adaptive gravitational constants”. Expert Systems with Applications, Vol. 152, pages 1-18, DOI: https://doi.org/10.1016/j.eswa.2020.113396. (SCIE, Q1, IF: 7.5)
Gupta, S., Deep, K., Mirjalili, S., & Kim, J. H. (2020). “A modified sine cosine algorithm with novel transition parameter and mutation operator for global optimization”. Expert Systems with Applications, Vol. 154, pages 1-21, DOI: https://doi.org/10.1016/j.eswa.2020.113395. (SCIE, Q1, IF: 7.5)
Gupta, S., Deep, K., Heidari, A. A., Moayedi, H., & Wang, M. (2020). “Opposition-based learning Harris hawks optimization with advanced transition rules: Principles and analysis”. Expert Systems with Applications, Vol. 158, pages 1-23, DOI: https://doi.org/10.1016/j.eswa.2020.113510. (SCIE, Q1, IF: 7.5)
Gupta, S., & Deep, K. (2020). “A memory-based grey wolf optimizer for global optimization tasks”. Applied Soft Computing, Vol. 93, pages 1-31, DOI: https://doi.org/10.1016/j.asoc.2020.106367. (SCIE, Q1, IF: 6.6)
Gupta, S., Deep, K., & Engelbrecht, A. P. (2020). “A memory guided sine cosine algorithm for global optimization”. Engineering Applications of Artificial Intelligence, Vol. 93, pages 1-19, DOI: https://doi.org/10.1016/j. engappai.2020.103718. (SCIE, Q1, IF: 8.0)
Gupta, S., Deep, K., & Mirjalili, S. (2020). “An efficient equilibrium optimizer with mutation strategy for numerical optimization”. Applied Soft Computing, Vol. 96, pages 1-21, DOI: https://doi.org/10.1016/j.asoc.20 20.106542. (SCIE, Q1, IF: 6.6)
Gupta, S., & Deep, K. (2020). “Hybrid sine cosine artificial bee colony algorithm for global optimization and image segmentation”. Neural Computing and Applications, Vol. 32, pages 9521-9543, DOI: https://doi.org/10.1007/s00521-019-04465-6. (Scopus, Q1)
Gupta, S., Deep, K., Heidari, A. A., Moayedi, H., & Chen, H. (2021). “Harmonized salp chain-built optimization”. Engineering with Computers, Vol. 37, pages 1049-1079, DOI: https://doi.org/10.1007 /s00366-019-00871-5. (SCIE, Q1, IF: 4.9)
Gupta, S., Deep, K., Moayedi, H., Foong, L. K., & Assad, A. (2021). “Sine cosine grey wolf optimizer to solve engineering design problems”. Engineering with Computers, Vol. 37, pages 31233149, DOI: https://doi.org/10.1007/s00366-020-00996-y. (SCIE, Q1, IF: 4.9)
Gupta, S., Abderazek, H., Yıldız, B. S., Yildiz, A. R., Mirjalili, S., & Sait, S. M. (2021). “Comparison of metaheuristic optimization algorithms for solving constrained mechanical design optimization problems”. Expert Systems with Applications, Vol. 183, pages 1-20, DOI: https://doi.org/10.1016/j.es wa.2021.115351. (SCIE, Q1, IF: 7.5)
Kardani, N., Bardhan, A., Gupta, S., Samui, P., Nazem, M., Zhang, Y., & Zhou, A. (2022). “Predicting permeability of tight carbonates using a hybrid machine learning approach of modified equilibrium optimizer and extreme learning machine”. Acta Geotechnica, Vol. 17, pages 1239–1255, DOI: https://doi.org/10.1007/s114 40-021-01257-y. (SCIE, Q1, IF: 5.7)
Bardhan, A., GuhaRay, A., Gupta, S., Pradhan, B., & Gokceoglu, C. (2022). “A novel integrated approach of ELM and modified equilibrium optimizer for predicting soil compression index of subgrade layer of Dedicated Freight Corridor”. Transportation Geotechnics, Vol. 32, pages 1-21, DOI: https://doi.org/10.1016/j.trgeo.2021.100678. (SCIE, Q1, IF: 5.5)
Gupta, S. (2022). “Enhanced harmony search algorithm with non-linear control parameters for global optimization and engineering design problems”. Engineering with Computers, Vol. 38, pages 3539-3562, DOI: https://doi.org/10.1007/s00366-021-01467-8. (SCIE, Q1, IF: 7.3)
Gupta, S. (2022). “Enhanced sine cosine algorithm with crossover: A comparative study and empirical analysis”. Expert Systems with Applications, Vol. 198, pages 1-20, DOI: https://doi.org/10.1016/j. eswa.2022.116856. (SCIE, Q1, IF: 7.5)
Gupta, S., Zhang, Y., & Su, R. (2022). “Urban traffic light scheduling for pedestrian-vehicle mixedf low networks using discrete sine cosine algorithm and its variants”. Applied Soft Computing, Vol. 120, pages 1-25, DOI: https://doi.org/10.1016/j.asoc.2022.108656. (SCIE, Q1, IF: 6.6)
Gupta, S., Rong, S. & Singh, S. (2022). “Diversified sine cosine algorithm based on differential evolution for multidimensional knapsack problem”. Applied Soft Computing, Vol. 130, pages 1-23, DOI: https://doi.org/10.1016/j.asoc.2022.109682. (SCIE, Q1, IF: 6.6)
Gupta, S., & Su, R. (2022). “An efficient differential evolution with fitness-based dynamic mutation strategy and control parameters”. Knowledge-Based Systems, Vol. 251, pages 1-27, DOI: https://doi.org/10.1016/j.kn osys.2022.109280. (SCI, Q1, IF: 7.6)
Gupta, S., Singh, S., Rong, S., Gao, S., & Bansal, J. C. (2023). “Multiple Elite Individual Guided Piecewise Search-Based Differential Evolution”. IEEE/CAA Journal of Automatica Sinica, Vol. 10, pages 135-158, DOI: https://doi.org/10.1109/JAS.2023.123018. (SCIE, Q1, IF: 19.2)
Gupta, S., & Rong, S. (2023). “Multiple individual guided differential evolution with time varying and feedback information-based control parameters”. Knowledge-Based Systems, Vol. 259, pages 1-35, DOI: https://doi.org/10.1016/j.knosys.2022.110091. (SCI, Q1, IF: 7.6)
Gupta, S., Weihua, S., Zhang, Y., & Su, R. (2023). “Differential evolution-driven traffic light scheduling for vehicle-pedestrian mixed-flow networks”. Knowledge-Based Systems, Vol. 274, pages 1-15, DOI: https://doi.org/10.1016/j.knosys.2023.110636. (SCI, Q1, IF: 7.6)
Gupta, S., & Su, R. (2023). “Diversity-enhanced modified sine cosine algorithm and its application in solving engineering design problems”. Journal of Computational Science, Vol. 72, pages 1-24, DOI: https://doi.org/10.1016/j.jocs.2023.102105. (SCIE, Q2, IF: 3.7)
Gupta, S., Zhang, Y., & Su, R. (2024). “Discrete grey wolf optimizer for solving urban traffic light scheduling problem”. Arabian Journal for Science and Engineering, Vol. 50, pages 11727–11755. DOI: https://doi.org/10.1007/s13369-024-09589-z ((SCI, Q1, IF: 2.9)
Gupta, S., & Gupta, S. (2024). “Fitness and historical success information-assisted binary particle swarm optimization for feature selection”, Volume 306, Knowledge-Based Systems, Vol. 306, Elsevier. DOI: https://doi.org/10.1016/j.knosys.2024.112699. (SCI, Q1, IF: 7.6)
Gupta, S., Kumar, A., Kumar, V., Singh, S., & Gautam, M. (2024). “Autonomous underwater vehicle path planning using fitness-based differential evolution algorithm”, 102498, Journal of Computational Science, Vol. 85, Elsevier. DOI: https://doi.org/10.1016/j.jocs.2024.102498. (SCI, Q2, IF: 3.7)
Xu, W., Song, Y., Gupta, S., Jia, D., Tang, J., Lei, Z., & Gao, S. (2025). “Dmixnet: a dendritic multi-layered perceptron architecture for image recognition”, Artificial Intelligence Review, Vol 58, Springer. DOI: https://doi.org/10.1007/s10462-025-11123-y (SCI, Q1, IF: 13.9)
Gupta, S., Sing, S., & Gao, S. (2025). “Fitness and Collaborative Information-Driven Differential Evolution Algorithm for Bound-Constrained and Real-World Application Problems”. Arabian Journal for Science and Engineering, Vol. 50, pages 16017–16051, Springer. DOI: https://doi.org/10.1007/s13369-025-10081-5 (SCI, Q1, IF: 2.9)
Gupta, S., Dwivedi, B., & Kumar, V. (2025). “Ensemble Mutation and Multi-Population-Driven Differential Evolution for Numerical Optimization and Feature Selection of Breast Cancer”. Computers in Biology and Medicine, Vol. 194, Elsevier. DOI: https://doi.org/10.1016/j.compbiomed.2025.110495 (SCI, Q1, IF: 6.3)
Gupta, S., Singh, S., & Kumar, V. (2025). “A reinforcement learning-assisted ensemble differential evolution approach for 3D AUV path planning”. Ships and Offshore Structures, Taylor and Francis. DOI: https://doi.org/10.1080/17445302.2025.2569424. (SCI, Q2, IF: 1.7)
Gupta, S., & Sahu, D. (2025). “Diversified clustering and archive pattern-based differential evolution for feature selection problems”. Cluster Computing, Vol. 29, Springer. DOI: https://doi.org/10.1007/s10586-025-05806-y. (SCI, Q1, IF: 4.1)
Gupta, S., & Gautam, K. (2025). “Enhanced Cooperative Learning and Local Search Integrated Particle Swarm Optimization for Global Optimization and Coverage Enhancement in Wireless Sensor Network”. Swarm and Evolutionary Computation, Vol. 100, Elsevier. DOI: https://doi.org/10.1016/j.swevo.2025.102262 (SCI, Q1, IF: 8.5)
Gupta, S., &Zhang, Y.(2025). “Development of metaheuristic algorithm-based approach for solving multi-bus dispatching and boarding management problem”. Evolutionary Intelligence, Springer. DOI: https://doi.org/10.1007/s12065-025-01124-9 (Scopus, Q2, IF: 2.6)

Conference Proceedings:

Gupta, S., & Deep, K. (2017). Performance of grey wolf optimizer on large scale problems. In AIP conference proceedings (Vol. 1802, No. 1, p. 020005). AIP Publishing LLC. DOI: https://doi.org/10.1 063/1.4973255.
Gupta, S., & Deep, K. (2019). Hybrid Grey Wolf Optimizer with mutation operator. In Soft computing for problem solving (pp. 961-968). Springer, India. DOI: https://doi.org/10.1007/978981-13-1595-4 75.
Gupta, S., & Deep, K. (2019). Improved grey wolf optimizer based on opposition-based learning. In Soft computing for problem solving (pp. 327-338). Springer, India. DOI: https://doi.org/10.1007/978981-13-1595-4 26.
Gupta, S., Deep, K., & Assad, A. (2020). Reliability–redundancy allocation using random walk gray wolf optimizer. In Soft computing for problem solving (pp. 941-959). Springer, India. DOI: https://doi.org/10.1007/978-981-15-0035-0 75.
Gupta, S., Kumar, V., Sahu, D., & Yadav, S. (2025). “Intelligent Control of Autonomous Underwater Vehicle for 3D Path Planning using Enhanced Subpopulation-Based Differential Evolution Algorithm”. International Conference on Electrical and Electronics Engineering (ICE3-2025), MMMUT, Singhariya, Kunraghat, Gorakhpur, India during 19- 20 September 2025, (Accepted).
Gautam, K., & Gupta, S. (2025). “Evolutionary State and Dual Sub-Swarm Assisted Particle Swarm Optimization for Image Thresholding Problem. IEEE International Conference on Recent Advances in Computing and Systems (ReACS2025). (Accepted), ABV-IIITM Gwalior, India during 19-20 December 2025.