| A real coded genetic algorithm for solving integer and mixed integer optimization problems K Deep, KP Singh, ML Kansal, C Mohan Applied Mathematics and Computation 212 (2), 505-518, 2009 | 882 | 2009 |
| A new crossover operator for real coded genetic algorithms K Deep, M Thakur Applied mathematics and computation 188 (1), 895-911, 2007 | 548 | 2007 |
| A new mutation operator for real coded genetic algorithms K Deep, M Thakur Applied mathematics and Computation 193 (1), 211-230, 2007 | 477 | 2007 |
| A novel random walk grey wolf optimizer S Gupta, K Deep Swarm and evolutionary computation 44, 101-112, 2019 | 381 | 2019 |
| A hybrid self-adaptive sine cosine algorithm with opposition based learning S Gupta, K Deep Expert Systems with Applications 119, 210-230, 2019 | 267 | 2019 |
| A modified binary particle swarm optimization for knapsack problems JC Bansal, K Deep Applied Mathematics and Computation 218 (22), 11042-11061, 2012 | 256 | 2012 |
| Optimal coordination of over-current relays using modified differential evolution algorithms R Thangaraj, M Pant, K Deep Engineering Applications of Artificial Intelligence 23 (5), 820-829, 2010 | 213 | 2010 |
| Improved sine cosine algorithm with crossover scheme for global optimization S Gupta, K Deep Knowledge-Based Systems 165, 374-406, 2019 | 178 | 2019 |
| A survey on parallel particle swarm optimization algorithms S Lalwani, H Sharma, SC Satapathy, K Deep, JC Bansal Arabian Journal for Science and Engineering 44, 2899-2923, 2019 | 149 | 2019 |
| A memory-based grey wolf optimizer for global optimization tasks S Gupta, K Deep Applied Soft Computing 93, 106367, 2020 | 140 | 2020 |
| A hybrid harmony search and simulated annealing algorithm for continuous optimization A Assad, K Deep Information Sciences 450, 246-266, 2018 | 125 | 2018 |
| Mean particle swarm optimisation for function optimisation K Deep, JC Bansal International Journal of Computational Intelligence Studies 1 (1), 72-92, 2009 | 123 | 2009 |
| A modified sine cosine algorithm with novel transition parameter and mutation operator for global optimization S Gupta, K Deep, S Mirjalili, JH Kim Expert Systems with Applications 154, 113395, 2020 | 117 | 2020 |
| Novel inertia weight strategies for particle swarm optimization P Chauhan, K Deep, M Pant Memetic computing 5, 229-251, 2013 | 107 | 2013 |
| Quadratic approximation based hybrid genetic algorithm for function optimization K Deep, KN Das Applied Mathematics and Computation 203 (1), 86-98, 2008 | 106 | 2008 |
| Opposition-based learning Harris hawks optimization with advanced transition rules: principles and analysis S Gupta, K Deep, AA Heidari, H Moayedi, M Wang Expert Systems with Applications 158, 113510, 2020 | 102 | 2020 |
| Harmonized salp chain-built optimization S Gupta, K Deep, AA Heidari, H Moayedi, H Chen Engineering with Computers 37, 1049-1079, 2021 | 97 | 2021 |
| An efficient equilibrium optimizer with mutation strategy for numerical optimization S Gupta, K Deep, S Mirjalili Applied Soft Computing 96, 106542, 2020 | 97 | 2020 |
| Discrete Grey Wolf Optimizer for symmetric travelling salesman problem K Panwar, K Deep Applied Soft Computing 105, 107298, 2021 | 92 | 2021 |
| Performance of Laplacian biogeography-based optimization algorithm on CEC 2014 continuous optimization benchmarks and camera calibration problem V Garg, K Deep Swarm and Evolutionary Computation 27, 132-144, 2016 | 88 | 2016 |
Shubham GuptaAssistant Professor, Department of Mathematics, NIT Allahabad在 mnnit.ac.in 的电子邮件经过验证
