Ensemble sinusoidal differential covariance matrix adaptation with Euclidean neighborhood for solving CEC2017 benchmark problems

By Noor H. Awad, Mostafa Z. Ali, Ponnuthurai Nagaratnam Suganthan. IEEE Congress on Evolutionary Computation, 2017

457 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Theory and Mathematics, Numerical Analysis

View Paper: https://www.semanticscholar.org/paper/8231f4d48e697fc7c7adba2ad7ded010e645e30f

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. Francisco Herrera
2. Salvador Garcia
3. Swagatam Das
4. María del Mar Rueda
5. Jacinto Carrasco
6. Jiankai Xue
7. Bo Shen
8. Alberto Fernández

In Computational Theory and Mathematics

1. Swagatam Das
2. Salvador Garcia
3. Francisco Herrera
4. Jiankai Xue
5. Bo Shen
6. Enrique Herrera-Viedma
7. Pinar Çivicioglu
8. Ponnuthurai Nagaratnam Suganthan

In Numerical Analysis

1. Jiankai Xue
2. Swagatam Das
3. Bo Shen

Citations in the corpus

• Recent Trends in the Use of Statistical Tests for Comparing Swarm and Evolutionary Computing Algorithms: Practical Guidelines and a Critical Review (2020, methodology): “LSHADE-cnEpSin (LSCNE) [82]: New version of LSHADE-EpSin that uses an ensemble of sinusoidal approaches based on the current adaptation and a modification of the crossover operator with a covariance matrix.”
• Dung beetle optimizer: a new meta-heuristic algorithm for global optimization (2022, methodology): “To further verify the search performance of the DBO technique, a set of challenging test functions, CEC-BC-2017, is employed.”