Nature-Inspired Optimization Algorithms

By A. Vasuki. 2020

429 citations recorded by the source corpus.

Subfields: Artificial Intelligence

View Paper: https://www.semanticscholar.org/paper/f639e4e58decd2dd3b7208b4ef2a4dd3e3ca7a0c

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. Xin-She Yang
2. Arpan Kumar Kar
3. Xingshi He
4. Seyed Mohammad Mirjalili
5. Seyedali Mirjalili
6. Amir H. Gandomi
7. Iztok Fister
8. Tansel Dökeroğlu

Citations in the corpus

• Nature-Inspired Optimization Algorithms: Challenges and Open Problems (2020, methodology): “In fact, a wide spectrum of SI-based algorithms have emerged in the last decades, including ant colony optimization (ACO) [Dorigo(1992)], particle swarm optimization (PSO) [Kennedy and Eberhart(1995)], bat algorithm (BA) [Yang(2010)], firefly algorithm (FA) [Yang(2009)], cuckoo search (CS) [Yang and”