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Dr. Jagdish Chand Bansal is an Associate Professor (Senior Grade) at South Asian University New Delhi and a Visiting Professor at Maths and Computer Science, Liverpool Hope University UK. He also holds a visiting professorship at NIT Goa, India. Dr. Bansal obtained his Ph.D. in Mathematics from IIT Roorkee. Before joining SAU New Delhi, he worked as an Assistant Professor at ABV- Indian Institute of Information Technology and Management Gwalior and BITS Pilani. His primary areas of interest are swarm intelligence and nature-inspired optimization techniques. Recently, he proposed a fission-fusion social structure based optimization algorithm, Spider Monkey Optimization (SMO), which is being applied to various problems in the engineering domain. He has published over 70 research papers in various international journals/conferences. He is the Section Editor (editor-in-chief) of the journal MethodsX published by Elsevier. He is the series editor of the four Springer book series AIS, SADIC, ISTC and SST published by Springer. He is also the Associate Editor of Engineering Applications of Artificial Intelligence (EAAI) and ARRAY published by Elsevier. He is the general secretary of the Soft Computing Research Society (SCRS). He has also received Gold Medal at UG and PG levels.
Optimization; Computational Intelligence; Swarm Intelligence; Soft Computing
Research Profiles
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Shitu Singh, Jagdish Chand Chand Bansal, A modified grey wolf optimizer for wind farm layout optimization problem", accepted, International Journal of System Assurance Engineering and Management, 10.1007/s13198-024-02462-0 | Impact Factor: 1.6 (Q2)
Prathu Bajpai, Jagdish Chand Chand Bansal, Voronoi Tessellations based Simple Optimizer, Information Sciences, https://doi.org/10.1016/j.ins.2024.120795 | Impact Factor: 8.1 (Q1)
Shitu Singh, Susheel Kumar Joshi, Jagdish Chand Bansal, StableGWO: A grey wolf optimizer with von Neumann stability criteria, Journal of Information & Optimization Sciences (accepted 2021) DOI : 10.47974/JIOS-1361. | Impact Factor: 1.4 (Q2)
Sakshi Shringi, Harish Sharma, Pushpa Narayan Rathie, Jagdish Chand Bansal, Atulya Nagar & Daya Lal Suthar (2024) Predicting COVID-19 outbreak in India using modified SIRD model, Applied Mathematics in Science and Engineering, 32:1, DOI: 10.1080/27690911.2024.2305191 | Impact Factor 1.3 | Q2
A.M. Mohiuddin, Jagdish Chand Bansal, An improved linear prediction evolution algorithm based on topological opposition-based learning for optimization, MethodsX (2023), doi: https://doi.org/10.1016/j.mex.2023.102511 | Impact Factor 1.9 | Q2
Mohiuddin A M; Bansal, Jagdish Chand, An improved linear prediction evolution algorithm based on nonlinear least square fitting model for optimization, Soft Computing, 27, 14019–14044 (2023). https://doi.org/10.1007/s00500-023-08500-6 | Impact Factor: 3.732 | Q2
Gupta, Shubham ; Singh, Shitu ; Su, Rong; Gao, Shangce ; Bansal, Jagdish Chand, Multiple Elite Individual Guided Piecewise Search-Based Differential Evolution, IEEE/CAA Journal of Automatica Sinica, vol. 10, no. 1, pp. 135-158, January 2023, doi: 10.1109/JAS.2023.123018. | Impact Factor: 7.847 | Q1
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Jagdish Chand Bansal, Nikhil Sethi, Ogbonnaya Anicho and Atulya Nagar, Drone Flocking Optimization using NSGA-II and Principal Component Analysis, Swarm Intelligence, 17, 63–87 (2023). https://doi.org/10.1007/s11721-022-00216-x | Impact factor: 3.727 | Q2 |
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Probhat Pachung, Jagdish Chand Bansal, An improved Tangent Search Algorithm, MethodsX (2022), doi: https://doi.org/10.1016/j.mex.2022.101839 . |
Shitu Singh, Jagdish Chand Bansal: "Mutation-driven Grey Wolf Optimizer with Modified Search Mechanism", Expert Systems With Applications, 194 (2022): 116450 https://doi.org/10.1016/j.eswa.2021.116450 | Impact factor 8.665 | Q1
Sakshi Shringi, Harish Sharma, Pushpa Narayan Rathie, Jagdish Chand Bansal, Atulya Nagar, Modified SIRD Model for COVID-19 Spread Prediction for Northern and Southern States of India, Chaos, Solitons & Fractals, Volume 148, 2021, 111039, https://doi.org/10.1016/j.chaos.2021.111039 | Impact Factor- 9.922 | Q1
Vishal Chaudhary, Hari Mohan Dubey, Manjaree Pandit, Jagdish Chand Bansal, Multi-area economic dispatch with stochastic wind power using Salp Swarm Algorithm, Array, Volume 8, 2020, 100044, https://doi.org/10.1016/j.array.2020.100044.
Joshi, S.K., Gopal, A., Singh, S. et al. A novel neighborhood archives embedded gravitational constant in GSA. Soft Comput 25, 6539–6555 (2021). https://doi.org/10.1007/s00500-021-05648-x | Impact Factor 3.732 | Q2
Jagdish Chand Bansal, Shitu Singh: "A better exploration strategy in Grey Wolf Optimizer", Journal of Ambient Intelligence and Humanized Computing, 12, 1099–1118 (2021 | Impact factor 3.662 | Q1
Susheel Kumar Joshi, Jagdish Chand Bansal: "Parameter Tuning for Meta-heuristics", Knowledge-Based Systems, 189 (2020): 105094 | Impact Factor 8.139 | Q1
Anshul Gopal, Mohammad Mahdi Sultani, Jagdish Chand Bansal: "On Stability Analysis of Particle Swarm Optimization Algorithm", Arabian Journal for Science and Engineering 45, 2385–2394 (2020) | Impact Factor: 2.807 | Q1
Soniya Lalwani, Harish Sharma, Suresh Chandra Satapathy, Kusum Deep, Jagdish Chand Bansal: "A Survey on Parallel Particle Swarm Optimization Algorithms", Arabian Journal for Science and Engineering, 44, 2899–2923 (2019) | Impact Factor: 2.807 | Q1
Jagdish Chand Bansal, Anshul Gopal, Atulya K Nagar: "Analysing convergence, consistency and trajectory of Artificial Bee Colony Algorithm", IEEE Access vol. 6, pp. 73593-73602, 2018 | Impact Factor: 3.476 |Q1
Sandeep Kumar, Basudev Sharma, Vivek Kumar Sharma, Harish Sharma, Jagdish Chand Bansal: "Plant Leaf Disease Identification using Exponential Spider Monkey Optimization", Sustainable Computing-Informatics and Systems, 2018 | Impact Factor: 4.923 | Q1
Nirmala Sharmaa, Harish Sharma, Ajay Sharma, and Jagdish Chand Bansal: "Grasshopper inspired artificial bee colony algorithm for numerical optimization", Journal of Experimental & Theoretical Artificial Intelligence, 2018 | Impact Factor: 2.296 | Q3
Pushpa Farswan, Jagdish Chand Bansal: "Fireworks-inspired biogeography-based optimization", Soft Computing, 23, pages7091–7115(2019) | Impact Factor: 3.732 | Q2
Jagdish Chand Bansal, Pushpa Farswan, Atulya Kumar Nagar: "Design of wind farm layout with non-uniform turbines using fitness difference based BBO", Engineering Applications of Artificial Intelligence, Volume 71, Pages 45-59, 2018 | Impact Factor: 7.802 | Q1
Jagdish Chand Bansal, Anshul Gopal, Atulya Kumar Nagar: "Stability Analysis of Artificial Bee Colony Optimization Algorithm", Swarm and Evolutionary Computation, Volume 41, Pages 9-19, 2018 | Impact Factor: 10.267 | Q1
Jagdish Chand Bansal, Susheel Kumar Joshi, Atulya Kumar Nagar: "Fitness Varying Gravitational Constant in GSA", Applied Intelligence, 48, pages3446–3461(2018) | Impact Factor: 5.019 | Q2
Jagdish Chand Bansal, Susheel Kumar Joshi, Harish Sharma: "Modified global best artificial bee colony for constrained optimization problems", Computers & Electrical Engineering, Volume 67, Pages 365-382, 2018 | Impact Factor: 4.152 | Q1
Shimpi Singh Jadon, Ritu Tiwari, Harish Sharma and Jagdish Chand Bansal: "Hybrid Artificial Bee Colony Algorithm with Differential Evolution", Applied Soft Computing, Volume 58, Pages 11-24, 2017 | Impact Factor: 8.263 | Q1
Jagdish Chand Bansal and Pushpa Farswan: "Wind farm layout using Biogeography Based Optimization", Renewable Energy (2017), Volume 107, Pages 386-402 | Impact Factor: 8.634 | Q1
Kavita Sharma, Kusum Deep, Jagdish Chand Bansal, Improving the local search ability of Spider Monkey Optimization algorithm using Quadratic Approximation for unconstrained optimization, Computational Intelligence (2017), Volume33, Issue2, 2017, Pages 210-240 | Impact Factor: 2.142 | Q2
Jagdish Chand Bansal, Pushpa Farswan, A novel Disruption in Biogeography-Based Optimization with application to optimal power flow problem, Applied Intelligence, 46, pages 590–615(2017) 46: 590 | Impact Factor: 5.019 | Q2
Ajay Sharma · Harish Sharma · Annapurna Bhargava · Nirmala Sharma · Jagdish Chand Bansal: "Optimal placement and sizing of capacitor using Limacon inspired Spider Monkey Optimization Algorithm", Memetic Computing, 9, pages311–331(2017) | Impact Factor: 3.577 | Q1
Shimpi Singh Jadon, Jagdish Chand Bansal and Ritu Tiwari: "Escalated convergent Artificial Bee Colony", Journal of Experimental & Theoretical Artificial Intelligence 28.1-2 (2016): 181-200. | Impact Factor: 2.296 | Q3
Jagdish Chand Bansal, Harish Sharma, K V Arya, Kusum Deep, Millie Pant: "Self-adaptive artificial bee colony Optimization", Optimization, Volume 63, Issue 10, 1513--1532 (2014) Taylor & Francis. | Impact Factor: 2.456 | Q1
Jagdish Chand Bansal, Harish Sharma, Shimpi Singh Jadon, Maurice Clerc: "Spider Monkey Optimization algorithm for numerical optimization". Memetic Computing 6(1): 31-47 (2014). | Impact Factor: 3.577 | Q1
Jagdish Chand Bansal, Harish Sharma, Shimpi Singh Jadon: "Artificial bee colony algorithm: a survey". International Journal of Advanced Intelligence Paradigms 5(1/2): 123-159 (2013).
Jagdish Chand Bansal, Harish Sharma, Atulya Nagar, K. V. Arya: "Balanced artificial bee colony algorithm". International Journal of Artificial Intelligence and Soft Computing 3(3): 222-243 (2013).
Harish Sharma, Jagdish Chand Bansal, K. V. Arya: "Opposition based lévy flight artificial bee colony". Memetic Computing 5(3): 213-227 (2013). | Impact Factor: 3.577 | Q1
Jagdish Chand Bansal, Harish Sharma, K. V. Arya, Atulya Nagar: "Memetic search in artificial bee colony algorithm". Soft Computing. 17(10): 1911-1928 (2013). | Impact Factor: 3.732 | Q2
Harish Sharma, Jagdish Chand Bansal, K. V. Arya: "Power law-based local search in differential evolution", International Journal of Computational Intelligence Studies, Inderscience Publishers, 2(2), 90-112 (2013).
Jagdish Chand Bansal, Kusum Deep: "A Modified Binary Particle Swarm Optimization for Knapsack Problems". Applied Mathematics and Computation 218(22): 11042-11061 (2012). | Impact Factor: 4.397 | Q1
Harish Sharma, Jagdish Chand Bansal, K. V. Arya, Kusum Deep: "Dynamic Swarm Artificial Bee Colony Algorithm". IJAEC 3(4): 19-33 (2012).
DOI: 10.4018/jaec.2012100102
Kusum Deep, Jagdish Chand Bansal: "Solving Economic Dispatch Problems with Valve-point Effects using Particle Swarm Optimization". J. UCS 18(13): 1842-1852 (2012). | Impact Factor: 1.056
Jagdish Chand Bansal, Harish Sharma: "Cognitive learning in differential evolution and its application to model order reduction problem for single-input single-output systems". Memetic Computing 4(3): 209-229 (2012). Impact Factor: 3.577 | Q1
Harish Sharma, Jagdish Chand Bansal, K. V. Arya: "Fitness based Differential Evolution". Memetic Computing 4(4): 303-316 (2012). Impact Factor: 3.577 | Q1
Harish Sharma, Jagdish Chand Bansal, K. V. Arya: "Self balanced differential evolution", Journal of Computational Science, Elsevier, (2012). | Impact Factor: 3.817 | Q1
Kusum Deep, Jagdish Chand Bansal: "Hybridization of Particle Swarm Optimization with Quadratic Approximation", OPSEARCH (Springer Publication), 46(1): 3-24 (2009)
Kusum Deep, Jagdish Chand Bansal: "Mean Particle Swarm Optimization for Function Optimization", Int. J. Computational Intelligence Studies, 1(1): 72–92 (2009)
Harish Sharma, Jagdish Chand Bansal, K. V. Arya: "Power Law based Local Search in Artificial Bee Colony", International Journal of Artificial Intelligence and Soft Computing, Inderscience, 4(2): 164-194, 2014.
Harish Sharma, Jagdish Chand Bansal, K.V. Arya, Xin-She Yang: "Levy Flight Artificial Bee Colony", International Journal of system sciences, Taylor and Francis 2016 Impact Factor 2.285 | Q2
Madhuri Arya, Kusum Deep, Jagdish Chand Bansal: "A Nature Inspired Adaptive Inertia weight in Particle Swarm Optimization", International Journal of Artificial Intelligence and Soft Computing, Inderscience., 2014
Shimpi Singh Jadon, Jagdish Chand Bansal, Ritu Tiwari, Harish Sharma: "Artificial bee colony algorithm with global and local neighborhoods", International Journal of Systems Assurance Engineering and Management, (2014). https://doi.org/10.1007/s13198-014-0286-6
Jagdish Chand Bansal, Shimpi Singh Jadon, Ritu Tiwari, Deep Kiran, B K Panigrahi: "Optimal Power flow Analysis using Artificial Bee Colony Algorithm with Global and Local Neighborhoods", International Journal of Systems Assurance Engineering and Management, (2017) 8(Suppl 4): 2158. https://doi.org/10.1007/s13198-014-0321-7
Shimpi Singh Jadon, Jagdish Chand Bansal, Ritu Tiwari, Harish Sharma: "Accelerating Artificial Bee Colony Algorithm with Adaptive Local Search", Memetic Computing, (2015) 7: 215. https://doi.org/10.1007/s12293-015-0158-x | Imapct Factor: 5.9 | Q1
Kavita Sharma, Varsha Chhamunya, P C Gupta, Harish Sharma, Jagdish Chand Bansal, Fitness based particle swarm optimization, International Journal of System Assurance Engineering and Management, 2015, Volume 6, Issue 3, pp 319-329
Ajay Sharma, Harish Sharma, Annapurna Bhargava, Nirmala Sharma, Jagdish Chand Bansal, Optimal Power Flow Analysis using Levy Flight Spider Monkey Optimization Algorithm" International Journal of Artificial Intelligence and Soft Computing (IJAISC), Jan 2016, Vol. 5, Issue 4, pp. 320-352
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