Comparative Analysis of Low Discrepancy Sequence-Based Initialization Approaches Using Population-Based Algorithms for Solving the Global Optimization Problems

• Main Authors: Waqas Haider Bangyal, Kashif Nisar, Ag. Asri Bin Ag. Ibrahim, Muhammad Reazul Haque, Joel J. P. C. Rodrigues, Danda B. Rawat
• Format: Article
• Language: English; English
• Published: Multidisciplinary Digital Publishing Institute (MDPI) 2021
• Subjects: Q1-390 Science (General); QA75.5-76.95 Electronic computers. Computer science
• Online Access: https://eprints.ums.edu.my/id/eprint/32027/1/Comparative%20Analysis%20of%20Low%20Discrepancy%20Sequence-Based%20Initialization%20Approaches%20Using%20Population-Based%20Algorithms%20for%20Solving%20the%20Global%20Optimization%20Problems.pdf; https://eprints.ums.edu.my/id/eprint/32027/2/Comparative%20Analysis%20of%20Low%20Discrepancy%20Sequence-Based%20Initialization%20Approaches%20Using%20Population-Based%20Algorithms%20for%20Solving%20the%20Global%20Optimization%20Problems1.pdf; https://eprints.ums.edu.my/id/eprint/32027/; https://www.mdpi.com/2076-3417/11/16/7591; https://doi.org/10.3390/app11167591

Metaheuristic algorithms have been widely used to solve diverse kinds of optimization problems. For an optimization problem, population initialization plays a significant role in metaheuristic algorithms. These algorithms can influence the convergence to find an efficient optimal solution. Mainly, f...