Citation

Pervaiz, Sobia and Haider Bangyal, Waqas and Ashraf, Adnan and Nisar, Kashif and Haque, Muhammad Reazul and Ag. Ibrahim, Ag. Asri and Chowdhry, B. S. and Rasheed, Waqas and Rodrigues, Joel J. P. C. and Etengu, Richard and Rawat, Danda B. (2022) Comparative Research Directions of Population Initialization Techniques using PSO Algorithm. Intelligent Automation & Soft Computing, 32 (3). pp. 1427-1444. ISSN 1079-8587, 2326-005X

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Abstract

In existing meta-heuristic algorithms, population initialization forms a huge part towards problem optimization. These calculations can impact variety and combination to locate a productive ideal arrangement. Especially, for perceiving the significance of variety and intermingling, different specialists have attempted to improve the presentation of meta-heuristic algorithms. Particle Swarm Optimization (PSO) algorithm is a populace-based, shrewd stochastic inquiry strategy that is motivated by the inherent honey bee swarm food search mechanism. Population initialization is an indispensable factor in the PSO algorithm. To improve the variety and combination factors, rather than applying the irregular circulation for the introduction of the populace, semi-arbitrary successions are more helpful. This examination presents a thorough overview of the different PSO initialization approaches which are dependent on semi-arbitrary successions systems. In this precise review, the best in class in the populace instatement is uncovered. The procedures are classified by utilizing a theoretical model that parts the cycle of populace introduction into two phases: that is, right now expressly or certainly utilized for reinstatement in every single present approach. The deliberate investigation unveils the potential examination zones of populace introduction and, furthermore, research holes, despite the fact that the fundamental center is to give the headings to future upgrade and advancement around there. This paper gives a deliberate study identified with this calculated model for the cutting edge of exploration, which is talked about in the predefined writing to date. The study is envisioned to be useful in examining the PSO algorithm in detail for the specialist. Likewise, the paper finds the proficiency of numerous quasi-random sequences (QRS) based on initialization approaches by looking at their exhibition analyzed for sixteen notable benchmark test problems.

Item Type:	Article
Uncontrolled Keywords:	Swarm intelligence, artificial intelligence, low discrepancy sequences, PSO
Subjects:	Q Science > Q Science (General) > Q300-390 Cybernetics
Divisions:	Faculty of Computing and Informatics (FCI)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	03 Feb 2022 03:13
Last Modified:	03 Feb 2022 03:13
URII:	http://shdl.mmu.edu.my/id/eprint/9927

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