Heterogeneous comprehensive learning particle swarm optimization with enhanced exploration and exploitation

By Nandar Lynn, Ponnuthurai Nagaratnam Suganthan. Swarm and Evolutionary Computation, 2015

475 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/9328dbc6b0896cb7560cea578223654b0d470cfd

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Swagatam Das
2. Ponnuthurai Nagaratnam Suganthan
3. Seyedali Mirjalili
4. Xin-She Yang
5. Seyed Mohammad Mirjalili
6. Francisco Herrera
7. Sankha Subhra Mullick
8. Pinar Çivicioglu

In Control and Systems Engineering

1. Swagatam Das
2. Sankha Subhra Mullick
3. Mengchu Zhou
4. Carlos Artemio Coello Coello
5. Ponnuthurai Nagaratnam Suganthan
6. Francisco Herrera
7. Xin-She Yang
8. Zeshui Xu

Citations in the corpus

• Comprehensive Learning Particle Swarm Optimization Algorithm With Local Search for Multimodal Functions (2019, background): “L-PSO [34], DNLPSO [29], HCLPSO [30], SRPSO [47], DMeSR-PSO [23], UPSO [48], FIPS [49], FDR-PSO [50], and CPSO-H [51].”
• Bio-inspired computation: Where we stand and what's next (2019, methodology): “Likewise, heterogeneous topologies [184] enforce different topological relationships (e.”
• Recent advances in differential evolution - An updated survey (2016, methodology): “The objective of using topologies in PSO is to slow down the rapid convergence of the particles towards the current gbest position [115].”