A survey of swarm intelligence for dynamic optimization: Algorithms and applications

By Michalis Mavrovouniotis, Changhe Li, Shengxiang Yang. Swarm and Evolutionary Computation, 2017

564 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Theory and Mathematics, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/57545bb0332adb2632701514fbeffea91c28eb66

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. Pinar Çivicioglu
8. Kashif Hussain

In Computational Theory and Mathematics

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

In Electrical and Electronic Engineering

1. Carlos Artemio Coello Coello
2. Ponnuthurai Nagaratnam Suganthan
3. Francisco Herrera
4. Swagatam Das
5. Xin-She Yang
6. Dervis Karaboga
7. Bilal Alatas
8. Bahriye Basturk

Citations in the corpus

• Bio-inspired computation: Where we stand and what's next (2019, background): “To this end, the interest has steered towards the use of self-adaptability in both active and passive approaches, always with bio-inspired solvers at their algorithmic core [77,84].”
• Archimedes optimization algorithm: a new metaheuristic algorithm for solving optimization problems (2020, methodology): “Additionally, there is constant influx of new ideas competing with classic methods like SA, PSO, ABC, and ACO while implemented on complex and highly non-linear optimization problems [36].”