An improved GA and a novel PSO-GA-based hybrid algorithm

By Xiaohu Shi, Yanchun Liang, H. P. Lee, Chun Lu, L. M. Wang. Information Processing Letters, 2005

365 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Biomedical Engineering, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/70a7550591005f50786c9f9ff2f92cee320fe1df

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. Henry Shu-Hung Chung
2. Christian Blum
3. Jun Zhang
4. Yu-hui Shi
5. Jakob Puchinger
6. Günther R. Raidl
7. Yun Li
8. Andrea Roli

In Biomedical Engineering

1. Christian Blum
2. Jun Zhang
3. Yu-hui Shi
4. Seyedali Mirjalili
5. Yun Li

In Control and Systems Engineering

1. Henry Shu-Hung Chung
2. Yu-hui Shi
3. Yun Li
4. Jun Zhang
5. Jingjing Li
6. Yue-jiao Gong
7. Günther R. Raidl
8. Christian Blum

Citations in the corpus

• SCA: A Sine Cosine Algorithm for solving optimization problems (2016, background): “There is a significant number of hybrid meta-heuristics in the literature such as: PSO-GA [36], PSO-ACO [37], ACO-GA [38], GA-DE [39], PSO-DE [40], ACO-DE [41], KH-CS [42], and KH-BBO [43].”
• Hybrid metaheuristics in combinatorial optimization: A survey (2011, background): “Another example concerns the work proposed in [56], where the authors propose the combination of genetic algorithms and particle swarm optimization.”
• Genetic Learning Particle Swarm Optimization (2016, methodology): “[15] proposed a PSO-GA-based hybrid algorithm by executing the two algorithms simultaneously.”