Optimization techniques play a crucial role in enhancing computational efficiency and accuracy across diverse applications. This bibliometric analysis explores the growing research on Pelican Optimization Techniques, focusing on their application in energy forecasting, medical diagnostics, object detection, wireless network optimization, and intelligent transport systems. The study, covering 2011 to 2024, analyses 20 documents from 19 sources, highlighting the 22.54% annual growth rate and contributions from 73 authors. Revealing that optimization algorithms are well-established, emerging themes like energy efficiency and real-time decision-making are gaining traction. The average citation per document of 5.2 reflects a moderate impact, while the document average age of 2.8 years suggests a contemporary and evolving research field. The study applied the use of MS Excel, R studio and Biblioshiny Applications that provided insights into collaboration patterns, thematic clusters, and future research directions, source of papers, country of authors, reinforcing the importance of optimization techniques in computational and engineering applications. The study provides a novel structured overview of methodologies in literature review, highlighting key innovations, challenges, and emerging trends. Findings suggest that the Pelican Optimization Algorithm significantly improves computational performance and decision-making accuracy, making it a promising tool for future research. This analysis contributes to the understanding of optimization advancements and their practical applications in real-world scenarios.
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