Exploring the Impact of Random Distribution Choices on Particle Swarm Optimization: An Initial Analysis

Author:

Kołodziejczyk Joanna,Tarasenko Yuliia,Sulikowski Piotr

Funder

Ministry of Education and Science of the Republic of Poland

Publisher

Elsevier BV

Subject

General Engineering

Reference25 articles.

1. Agushaka, J.O., Ezugwu, A.E., Abualigah, L., Alharbi, S.K., Khalifa, H.A.E.W., 2022. Efficient initialization methods for population-based metaheuristic algorithms: A comparative study. doi:10.1007/s11831-022-09850-4.

2. Studying the impact of initialization for population-based algorithms with low-discrepancy sequences;Ashraf;Applied Sciences (Switzerland),2021

3. Comparative analysis of low discrepancy sequence-based initialization approaches using population-based algorithms for solving the global optimization problems;Bangyal;Applied Sciences (Switzerland),2021

4. Efects of random values for particle swarm optimization algorithm;Dai;Algorithms,2018

5. Non-Uniform Random Variate Generation(originally published with;Devroye,1986

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