An exhaustive review of the metaheuristic algorithms for search and optimization: taxonomy, applications, and open challenges. - Kanchan Rajwar; Kusum Deep; Swagatam Das (Artif. Intell. Rev., 2023)

Q-Learning-Driven Framework for High-Dimensional Optimization Problems. - Kanchan Rajwar; Kusum Deep (CEC, 2024)

Investigating Structural Bias in Real-Coded Genetic Algorithms. - Kanchan Rajwar; Yogesh Kumar; Kusum Deep (GECCO Companion, 2024)

Application of Machine Learning in Agriculture: Recent Trends and Future Research Avenues. - Aashu; Kanchan Rajwar; Millie Pant; Kusum Deep (CoRR, 2024)

Uncovering structural bias in population-based optimization algorithms: A theoretical and simulation-based analysis of the Generalized Signature Test. - Kanchan Rajwar; Kusum Deep (Expert Syst. Appl., 2024)

Regenerative population strategy-I: A dynamic methodology to mitigate structural bias in metaheuristic algorithms. - Kanchan Rajwar; Kusum Deep (Inf. Sci., 2025)

Structural bias in metaheuristic algorithms: Insights, open problems, and future prospects. - Kanchan Rajwar; Kusum Deep (Swarm Evol. Comput., 2025)