PhD (EEE) Batch 2011
|Research Topic: Computational Intelligent Algorithms for scheduling on renewable energy systems
Research Summary: To develop and implement computational intelligence (CI) algorithms for unit commitment scheduling of renewable energy systems
- N. Lynn, P.N. Suganthan, “Comprehensive learning particle swarm optimizer with guidance vector selection”, in proceedings of IEEE Swarm Intelligence Symposium (SIS), pp. 80-84, Singapore, 2013.
- N. Lynn, P.N. Suganthan, “Distance-based Locally Informed Particle Swarm Optimizer with dynamic population size”, in proceedings of 18th Asia Pacific Symposium on Intelligent and Evolutionary Systems pp. 576-587,Singapore, 2014.
- N. Lynn, R. Mallipeddi, P.N. Suganthan, “Differential Evolution with Two Subpopulations”, in proceedings of 5th International Conference on Swarm, Evolutionary and Memetic Computing, India, 2014. (Application : unit commitment problem)
- N. Lynn, R. Mallipeddi, P.N. Suganthan, “Self-adaptive Differential Evolution with Ensembles of Strategies and Sampled Parameter Values for Unit Commitment”, in proceedings of 6th International Conference on Swarm, Evolutionary and Memetic Computing, India, 2015.
- N. Lynn, N, P. N. Suganthan, “Modified Artificial Bee Colony Algorithm with Comprehensive Learning Re-initialization Strategy,” in proceedings of IEEE International Conference on Systems, Man and Cybernetics, Hong Kong, 2015.