World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
39
Citations
8258
World Ranking
9614
National Ranking
101

Overview

Kusum Deep is affiliated with the Indian Institute of Technology Roorkee in India. Their research primarily focuses on computer science and engineering, with a significant emphasis on artificial intelligence and computational theory and mathematics. The subfields include industrial and manufacturing engineering, computer vision and pattern recognition, and electrical and electronic engineering.

The main topics in Kusum Deep's research portfolio cover metaheuristic optimization algorithms, advanced multi-objective optimization algorithms, evolutionary algorithms and their applications, vehicle routing optimization methods, advanced optimization algorithm research, advanced manufacturing and logistics optimization, and face and expression recognition.

Kusum Deep has contributed to several recent papers, including:

  • "An exhaustive review of the metaheuristic algorithms for search and optimization: taxonomy, applications, and open challenges" (2023), published in Artificial Intelligence Review
  • "A memory-based Grey Wolf Optimizer for global optimization tasks" (2020), published in Applied Soft Computing
  • "Discrete Grey Wolf Optimizer for symmetric travelling salesman problem" (2021), published in Applied Soft Computing
  • "A modified Sine Cosine Algorithm with novel transition parameter and mutation operator for global optimization" (2020), published in Expert Systems with Applications
  • "Opposition-based learning Harris hawks optimization with advanced transition rules: principles and analysis" (2020), published in Expert Systems with Applications

Frequent co-authors collaborating with Kusum Deep include Vanita Garg, Kanchan Rajwar, Shubham Gupta, Millie Pant, and Atulya K. Nagar.

Major publication venues for Kusum Deep's work include:

  • Expert Systems with Applications
  • International Journal of Systems Assurance Engineering and Management
  • SSRN Electronic Journal
  • Applied Soft Computing
  • Evolutionary Intelligence

Kusum Deep has published several books with prominent publishers such as Springer Nature and Springer International Publishing. These works include "Soft Computing for Problem Solving 2019" (2020), "Proceedings of International Conference on Scientific and Natural Computing" (2021), "Soft Computing for Problem Solving" (2021), "Design and Applications of Nature Inspired Optimization" (2022), and "Women in Soft Computing" (2023).

Best Publications

  • A real coded genetic algorithm for solving integer and mixed integer optimization problems

    Kusum Deep;Krishna Pratap Singh;M. L. Kansal;C. Mohan

  • A new crossover operator for real coded genetic algorithms

    Kusum Deep;Manoj Thakur

  • An exhaustive review of the metaheuristic algorithms for search and optimization: taxonomy, applications, and open challenges

    Unknown

  • A new mutation operator for real coded genetic algorithms

    Kusum Deep;Manoj Thakur

  • A novel Random Walk Grey Wolf Optimizer

    Shubham Gupta;Kusum Deep

  • A hybrid self-adaptive sine cosine algorithm with opposition based learning

    Shubham Gupta;Kusum Deep

  • A Modified Binary Particle Swarm Optimization for Knapsack Problems

    Jagdish Chand Bansal;Kusum Deep

  • Optimal coordination of over-current relays using modified differential evolution algorithms

    Radha Thangaraj;Millie Pant;Kusum Deep

  • Improved sine cosine algorithm with crossover scheme for global optimization

    Shubham Gupta;Kusum Deep

  • A memory-based Grey Wolf Optimizer for global optimization tasks

    Shubham Gupta;Kusum Deep

  • A Survey on Parallel Particle Swarm Optimization Algorithms

    Soniya Lalwani;Harish Sharma;Suresh Chandra Satapathy;Kusum Deep

  • A Hybrid Harmony search and Simulated Annealing algorithm for continuous optimization

    Assif Assad;Kusum Deep

  • Mean particle swarm optimisation for function optimisation

    Kusum Deep;Jagdish Chand Bansal

  • Discrete Grey Wolf Optimizer for symmetric travelling salesman problem

    Karuna Panwar;Kusum Deep

  • Novel inertia weight strategies for particle swarm optimization

    Pinkey Chauhan;Kusum Deep;Millie Pant

  • A modified Sine Cosine Algorithm with novel transition parameter and mutation operator for global optimization

    Shubham Gupta;Kusum Deep;Seyedali Mirjalili;Joong Hoon Kim

  • Quadratic approximation based hybrid genetic algorithm for function optimization

    Kusum Deep;Kedar Nath Das

  • Opposition-based learning Harris hawks optimization with advanced transition rules: principles and analysis

    Shubham Gupta;Shubham Gupta;Kusum Deep;Ali Asghar Heidari;Ali Asghar Heidari;Hossein Moayedi

  • An efficient equilibrium optimizer with mutation strategy for numerical optimization

    Shubham Gupta;Kusum Deep;Seyedali Mirjalili

  • A self-organizing migrating genetic algorithm for constrained optimization

    Kusum Deep;Dipti

  • A memory guided sine cosine algorithm for global optimization

    Shubham Gupta;Kusum Deep;Andries P. Engelbrecht

  • Harmonized salp chain-built optimization

    Shubham Gupta;Kusum Deep;Ali Asghar Heidari;Ali Asghar Heidari;Hossein Moayedi

Frequent Co-Authors

Millie Pant
Millie Pant Indian Institute of Technology Roorkee
Ali Asghar Heidari
Ali Asghar Heidari National University of Singapore
Said Salhi
Said Salhi University of Kent
Hossein Moayedi
Hossein Moayedi Duy Tan University
Sushil Kumar
Sushil Kumar Central University of Haryana
Andries P. Engelbrecht
Andries P. Engelbrecht Stellenbosch University
Vaclav Snasel
Vaclav Snasel VSB – Technical University of Ostrava
Rajesh Kumar
Rajesh Kumar University of Johannesburg
Huiling Chen
Huiling Chen Wenzhou University

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