Studying the Impact of Initialization for Population-Based Algorithms with Low-Discrepancy Sequences

Studying the Impact of Initialization for Population-Based Algorithms with Low-Discrepancy Sequences

To solve different kinds of optimization challenges, meta-heuristic algorithms have been extensively used. Population initialization plays a prominent role in meta-heuristic algorithms for the problem of optimization. These algorithms can affect convergence to identify a robust optimum solution. To...

Full description

Bibliographic Details
Main Authors: Adnan Ashraf, Sobia Pervaiz, Waqas Haider Bangyal, Kashif Nisar, Ag. Asri Ag. Ibrahim, Joel j. P. C. Rodrigues, Danda B. Rawat
Format: Article
Language:English
Published: MDPI AG 2021-09-01
Series:Applied Sciences
Subjects:
Knuth sequence
premature convergence
quasi-random sequences
Torus sequence
training of artificial neural network
WELL sequence
Online Access:https://www.mdpi.com/2076-3417/11/17/8190

Internet

https://www.mdpi.com/2076-3417/11/17/8190

Similar Items